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Describe a best friend essay

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Introduction Windows Communication Foundation. Au court de cet article je vais vous prsenter Windows Communication Foundation, ou WCF, qui est une des grandes nouveauts du Framework.Net 3.0. Describe A Best Friend? WCF fournit un modle de programmation unifie pour construire des applications distribues, WCF va permettre de faire communiquer des composants applicatifs se trouvant sur une mme machine, mais le plus souvent sur diffrentes machines relies en rseau. N'hsitez pas commenter cet article ! Commentez. Article lu fois. Publié le 14 aot 2007. WCF, ou Windows Communication Foundation, est une des nouveauts majeures de la version 3.0 du Framework .Net. Essay On Overcoming Speaking? WCF fournit un modle de programmation unifie pour construire des applications distribues, WCF va nous permettre de faire communiquer des composants applicatifs se trouvant sur une mme machine, mais le plus souvent sur diffrentes machines relies en rseau.

Vous devez penser que cela n'a rien de rvolutionnaire et que cela existe depuis trs longtemps dj, et vous avez raison (Remoting, Web Services, COM+, MSMQ et d'autres encore), ce qui change ici, c'est qu'avec WCF nous pouvons faire communiquer les applications que nous crons avec toutes ces technologies, sans pour autant devoir adapter nos dveloppements de manire spcifique avec chacune. Friend? WCF va savoir interagir avec diffrentes technologies, et dtail trs important mes yeux, le code n'aura pas tre adapt et modifi en fonction du moyen de communication que vous choisirez. Un exemple simple pour mieux comprendre, vous crez une application qui communique par HTTP et SOAP, et que pour une raison ou une autre vous souhaitez communiquer en TCP et binaire, avec WCF vous ne changerez pas la moindre ligne de code de votre application. Writing? C'est une grande force de WCF, le code de votre application, son fonctionnement, sont dcoupls du moyen de communication utilis. A Best Friend Essay? Pour ceux qui ont dj fait du Remoting par exemple, vous devez apprcier cette caractristique. Bien qu'issu de la plateforme .Net et donc de l'environnement Windows, WCF a une vision plus large, et grce l'implmentation de nombreux standards cette technologie peut tre utilise pour communiquer avec des plateformes autres que Windows. Maintenant que vous voyez dans les trs grandes lignes ce qu'est WCF, entrons un peu plus dans le dtail.

L'lment central dans WCF est le service, voyons ce qui ce cache derrire ce terme qui est utilis dans de nombreux contextes diffrents en informatique. Sleep Deprivation? Pour vous donner une ide simple de ce qu'est un service WCF je vous propose d'imaginer un composant logiciel autonome, qui est capable d'effectuer des oprations et des communications au travers d'un rseau. Un service WCF est une entit logicielle implmentant un contrat, qui est une interface au sens objet du terme. Describe A Best Friend Essay? Cette interface reprend la liste des oprations que va exposer un service. Place? En fait plus prcisment, on describe a best friend dfinit un contrat par trois lettres, A, B et C. 10 Canadian Questions? A pour adresse, B pour Binding et C pour contrat. Commenons par prsenter l'adresse. Essay? Il s'agit simplement d'une URI qui dfinit o est joignable le service, cela peut tre par exemple une URL http comme l'adresse d'une file d'attente MSMQ… La nature de l'adresse dpend du protocole choisit et de l'infrastructure rseau. Le Binding est en fait la mthode, le protocole, utilis pour communiquer avec le service WCF. Outlines Paper? Le Framework .Net 3.0 nous fournit la base 9 bindings que l'on peut utiliser directement. A Best Friend? Comme nous le verrons plus tard, ces bindings prsentent des caractristiques diffrentes, offrent de nombreuses fonctionnalits avances et couvrent ainsi de nombreux scnarios d'utilisation. English? Cependant, dans l'optique de gnricit et d'ouverture de WCF il est tout fait possible si ncessaire d'utiliser ses propres bindings personnaliss avec vos protocoles maison.

Voici la liste des bindings inclus dans WCF : BasicHttpBinding WSHttpBinding WSDualHttpBinding WSFederationHttpBinding NetTcpBinding NetNamedPipeBinding NetMsmqBinding NetPeerTcpBinding MsmqIntegrationBinding. Et enfin, le contrat. Describe A Best Friend Essay? Comme nous l'avons vu prcdemment c'est un lment majeur du service WCF, c'est lui qui dfinit les oprations exposes par le service. Research Paper? Ce contrat indique quels sont les types et les paramtres employs par le service. Describe A Best Friend Essay? Un contrat est en fait une Interface, au sens objet du terme, dcore de quelques attributs spcifiant qu'il s'agit d'un contrat WCF.

Si vous avez compris l'ABC de WCF vous pouvez alors crer votre premier service sans difficult. Paper? C'est d'ailleurs ce que nous allons faire dans cet article, mais avant, nous allons examiner ce dont nous avons besoin pour crer des services WCF. Le Framework .Net en version 3.0 minimum Visual Studio 2005 ou version ultrieure (rien ne vous empche d'utiliser Notepad pour coder, mais restons raisonnables un instant s'il vous plait…) Les extensions WCF pour Visual Studio 2005 si vous l'utilisez videmment. Apres avoir install ces trois lments, vous tes prt crer votre premier service WCF. Describe A Best Friend Essay? Les liens pour tlcharger ces diffrents composants sont disponibles a la fin de cet article dans la section Ressources. Crons sans plus tarder notre premier service WCF. Pour cela il suffit de prparer un minimum Visual Studio et suivre l'ABC. Grade 10 Canadian Questions? Nous allons utiliser le namespace System.ServiceModel pour crer nos services WCF, il faut donc commencer par ajouter une rfrence vers l'assembly System.ServiceModel.dll. Describe A Best Essay? Ensuite, dans chaque fichier de code vous devez ajouter un Imports System.ServiceModel ou un using System.ServiceModel ; si vous utilisez VB.Net ou C#. Remarque : je pense que ce n'est pas forcement ncessaire de le prciser, mais dans le doute, comme tous les lments de la technologie .Net, WCF est utilisable avec n'importe quel langage compatible .Net, il en existe plus d'une trentaine. On Overcoming Of Public Speaking? Je me borne fournir mon code dans les deux principaux langages, mais si vous faites du Delphi .Net, du J#, du Cobol .Net ou je ne sais quel langage, Windows Communication Foundation est disponible.

C'est une des grandes forces de la technologie .Net. Visual Studio est dsormais prt. Describe A Best? Je ne l'ai pas prcis, mais votre service WCF peut tre cr dans n'importe quel type d'application (Console, WinForms, Web…). Describing? En disant cela je ne suis pas totalement prcis, car en fait, lorsque nous crons un service WCF nous le faisons dans une DLL, c'est par la suite que l'on choisira de l'intgrer dans un type d'application donn. A Best Essay? Il sera hberg (on dit host) par une autre application. Of Public? En effet, un service WCF en tant que tel (une DLL) n'est pas autonome et ncessite un hte pour s'excuter.

Pour permettre un dcoupage et une maintenance facile de notre service nous allons stocker notre interface dans une DLL, il faut donc pour cela crer un projet de type Bibliothque de classes. Comme vu prcdemment, l'lment central d'un service est son contrat. Describe Essay? Conceptuellement parlant, il est trs important de commencer par dfinir ce contrat, pralablement tout autre lment. Sleep Conclusion? Une fois le contrat tablit nous pouvons alors dfinir le reste. Info : au cours de cet article, nous allons crer un service qui sera capable d'effectuer des conversions montaires avec l'Euro et le Dollars. A Best? Par exemple en donnant un montant en Euros, le service nous renverra le montant quivalent en Dollars US, et inversement. Essay On Overcoming Fear Of Public? Je vous l'accorde ce service ne rvolutionnera pas le monde du logiciel, mais ce n'est pas l'objet de cet article. Notre service exposera donc deux mthodes principales qui sont EurosToUsDollars() et UsDollarsToEuros(), ces deux fonctions renverrons le montant stock dans une variable de type Decimal. Describe Friend Essay? Voici sans plus tarder a quoi va ressembler notre contrat : Vous voyez qu'en plus du code normal que l'on retrouve dans une interface .Net, il y a quelques attributs propres WCF que je vais vous prsenter. ServiceContract : cet attribut comme son nom l'indique, permet de dfinir cette interface en tant que contrat de service WCF, c'est--dire qu'un service WCF pourra exposer les oprations dfinies dans l'interface, condition que ces mthodes arborent l'attribut suivant.

OperationContract : cet attribut que l'on positionne au dessus de la signature de la mthode spcifie que la mthode concerne sera expose par le service. Research Paper? Une mthode peut trs bien ne pas avoir cet attribut positionn, mais dans ce cas elle ne sera pas expose par le service. Notre contrat, l'interface, est maintenant dfinit. Describe Friend? Il faut l'implmenter, pour cela nous allons ajouter un nouveau projet de type Bibliothque de classes notre solution Visual Studio. Grade 10 Canadian Essay Questions? Ce projet doit comporter une rfrence vers le projet contenant l'interface, il faut donc l'ajouter. Describe Friend? Il faut aussi ajouter dans le code un Imports ou using vers le namespace contenant l'interface. Research? C'est ici que nous allons rellement coder notre service.

Puisque cette classe implmente le contrat du service, l'interface, celle-ci doit en reprendre tous les membres. Friend Essay? Voici ce que pourrait tre le code de notre service de conversion montaire : Remarque : cette application n'tant la que pour illustrer la technologie il n'est pas idal, en effet, les taux de conversion sont en dur dans le code, ce qui vous le savez n'est absolument pas raliste puisque ces taux sont variables et changent en permanence… Ce qui serait par exemple possible de faire, c'est de relier notre service WCF un Web Service boursier qui nous permette de rcuprer intervalle rgulier le taux de conversion actualis. Freshman Research Paper? WCF sait parfaitement faire cela, et se connecter un Web Service est trs simple. A ce stade, notre service est termin, enfin presque, en effet celui-ci n'est pas autonome, il a besoin pour cela d'un hte sur lequel il pourra tre excut. A Best Friend? Cet hte peut tre n'importe quel type d'application .Net, un service Windows ou mme IIS 7.0 et le nouveau Windows Activation Service (WAS) ce qui permet de bnficier de la robustesse, de la tolrance aux pannes et des capacits de monte en charge du serveur d'applications (en effet, cela fait bien longtemps que IIS n'est plus un simple serveur Web) de Microsoft. Remarque : IIS 5.1 et 6.0 (c'est--dire respectivement IIS de Windows XP et 2003) peuvent hberger des services WCF mais avec une restriction; en effet ils devront utiliser HTTP pour les bindings, seul IIS 7.0 sait hberger des services WCF autres que HTTP (TCP, MSQM…). Pour ma dmonstration je vais employer une application Windows Forms, car c'est la mthode la plus approprie a mon avis pour ce genre de dmonstration. Questions? Voyons maintenant comment crer notre hte de service WCF.

Ce projet Windows Forms doit possder une rfrence vers System.ServiceModel et vers le projet contenant le service lui mme. Ce code introduit un nouvel objet, il s'agit du ServiceHost, qui comme sont nom l'indique est un hte de service. Describe Friend? Mais attention force d'employer le mot service toutes les sauces l'on s'y perd un peu. Composition Research Paper? Il ne s'agit pas d'un Web Service, ni d'un service Windows mais bel et bien d'un hte de service WCF. Describe? Nous voyons que cet objet ServiceHost est gnrique, on grade 10 canadian history questions spcifie son type lors de son instanciation. Describe A Best Friend? ServiceHost est du type de notre service que nous avons cod l'tape prcdente.

On voit ici une autre utilisation des Generics, qui est un lment indispensable dans l'architecture WCF. Maintenant que notre hte est instanci, il ne reste plus qu' le laisser communiquer, pour cela il suffit d'appeler la mthode Open(), la mthode Close() quand elle vous l'aurez compris, sert fermer les communications de notre service dans son hte. A cet instant le code de notre service est termin, vous pouvez fermer le dbogueur il ne sera plus utile:-)). Place? Mais il nous reste cependant une dernire tape raliser avant la mise en route de notre service WCF, il faut dfinir le A et le B, soit l'adresse et le binding. A Best Friend? Pour cela il y a deux manires de procder, depuis le code de l'hte ou depuis un fichier de configuration, c'est cette dernire solution que nous allons voir en dtail. Poverty Essay? L'une des forces de WCF c'est de sparer, de dcoupler, l'implmentation du service des protocoles et moyens de communications employs, donc dfinir le A et le B dans le code serait d'une certaine manire, aller contre la philosophie de WCF, mais sachez quand mme que c'est tout fait ralisable. Pour ajouter un fichier de configuration app.config il suffit d'ajouter un nouvel lment votre projet hte de service, Visual Studio possde un Template de tel fichier, mais vous pouvez trs bien l'diter vous-mme, il ne s'agit en effet ni plus ni moins que d'un simple fichier XML. Friend? Voici quoi ressemble un fichier de configuration pour un service WCF utilisant HTTP/SOAP sur le port 8018. Vous voyez apparaitre une nouvelle balise, inconnue jusqu'ici, ce qui est normale puisqu'elle est spcifique a WCF, il s'agit de la balise system.serviceModel, qui contient une balise services qui elle-mme contient une balise service, c'est ce niveau que nous allons dfinir le binding et l'adresse de notre service WCF.

Le nom du service est le nom complet (namespace + classe) de notre service, et le nom de l'endpoint est le nom complet du contrat de notre service, c'est--dire l'interface. Endpoint, vous avez dis Endpoint ? Voila encore un nouveau terme, un endpoint est tout simplement un point de terminaison de notre service, c'est--dire une voie par laquelle il peut communiquer, un endpoint est en fait dfinit par une adresse, ventuellement un port et un protocole. 10 Canadian History? Pour un mme service il est possible d'en dfinir plusieurs, ce qui implique que par exemple, un service WCF pourra communiquer en mme temps grce HTTP/SOAP, MSMQ et par TCP. Describe A Best Friend Essay? Le endpoint est l'lment stratgique du service WCF, c'est lui qui dfinit par quel biais va interagir notre service avec le monde extrieur, on research paper voit d'ailleurs qu'il centralise par le biais d'un simple fichier de configuration son propre ABC. A ce stade, nous avons ralis un service WCF, nous l'avons hberg et rendu oprationnel. Describe Essay? Voici le code complet du service WCF pour vous montrer quel point le code d'un service WCF est simple et court.

Je vous rappelle que pour les besoins de la dmonstration j'ai utilis une application Windows Forms pour hoster le service, mais cela pourrait tre n'importe quel type d'application Windows ou encore IIS 7.0 et le WAS. Nous avons dcoup notre service WCF en trois projets diffrents, l'interface, le service et son hte. Grade Essay Questions? Cela pourrait tre regroup dans un seul et mme projet, mais pour des raisons de clart, de scurit, de facilit et de maintenance je vous recommande de dcouper un service WCF en au moins trois projets (cela peut tre plus si vous utilisez d'autres objets mtiers), de plus, vous verrez bientt que cela prend tout son sens vis--vis du client de votre service, en terme de scurit et confidentialit de l'implmentation relle du service. 3. Describe A Best Friend Essay? Crons un client pour notre service WCF^ Il est certes intressant d'avoir un service WCF, mais faut il encore que celui-ci soit utilis. Outlines Research Paper? Pour cela nous allons crer un client en .Net, mais souvenez vous qu'il pourrait trs bien tre en Java, en C++ ou Python. A Best? Un des intrts des services WCF est qu'ils supportent de nombreux protocoles standards et ouverts et peuvent tre interoprables et donc fonctionner avec des clients ou d'autres services sur des plateformes diffrentes. Essay? Attention cependant, parmi les neufs bindings de bases inclus dans le Framework .Net 3.0, quatre (BasicHttpBinding, WSHttpBinding, WSDualHttpBinding, WSFederationHttpBinding) sont interoprables, les autres sont bass sur des technologies .Net et/ou Microsoft. Une fois de plus le client peut tre une application .Net de n'importe quel type, mon choix va se porter sur une application Windows Forms. Describe A Best Essay? Ajoutons donc un nouveau projet de ce type a notre solution. English Essay Describing Place? Ce projet doit avoir une rfrence vers l'interface, le contrat de notre service WCF, et une rfrence vers System.ServiceModel.

Remarque : vous comprenez ici l'intrt de dcouper notre service en plusieurs projets ; en effet, le client devra avoir connaissance de l'interface, donc si celle ci se trouve dans la mme DLL que le service lui-mme cela pose de srieux problmes de scurit, l'implmentation mme du service n'tant alors plus secrte, puisque distribue avec chaque client. Essay? De plus, sachez que potentiellement il est possible de ne pas fournir l'interface (le contrat) au client, celui-ci pourra gnrer le code ncessaire en rcuprant des mtadonnes relatives au service auprs de ce dernier. Pensez jouter les Imports et using ncessaires dans vos fichiers de code. English? L'objet central de notre client va tre le ChannelFactory, qui va permettre de crer un canal de communication pour communiquer avec le service. Describe Friend Essay? ChannelFactory est une fabrique de classe, c'est--dire un gnrateur de classe, une classe qui autorisera un client envoyer et/ou recevoir vers et depuis un service. English Essay? Voici le code qui nous permettra de crer ce canal de communication entre le client et le serveur, notez que cet objet est du type de notre interface, le contrat de notre service. Comme pour un service WCF, un client WCF utilise un fichier de configuration (qui comme pour le service peut tre remplac par un codage en dur dans l'application) qui va contenir l'ABC du service WCF, plus un nom que l'on donnera cette connexion.

Voici a quoi va ressembler le fichier de configuration de notre client. Comme nous l'avons vu un petit peu plus haut dans le code de cration du canal de communication, le nom de la connexion est employ en dur dans le code, ce nom peut tre utilis pour diffrencier les connexions du client, cela veut dire que par exemple chaque client pourra possder plusieurs connexions et utilisera l'une ou l'autre en fonction du contexte (connexion au rseau local, Internet…). Voyons maintenant comment utiliser les mthodes exposes par le service. Describe Friend Essay? Grce la fabrique de classes que nous avons instancie, nous allons gnrer un proxy fortement typ, qui nous permettra d'accder aux mthodes exposes par le service. Outlines Paper? Regardons un exemple nous montrant comment accder aux deux mthodes de notre service de conversion montaire. Voila, vous pouvez consommer votre service WCF depuis votre client. Describe A Best Friend? Tout ceci est relativement simple, et sachez que la technologie WCF est trs ouverte et hautement personnalisable. Research? Les possibilits sont extrmement nombreuses. Describe A Best? Pour finir, voici le code complet du client, vous voyez a quel point WCF nous mche le travail, accder un service au travers d'un rseau, ne prend que quelques lignes et cela quelque soit le protocole utilis…

J'espre qu'au travers de cet article, je vous aurai montr ce qu'est WCF, du moins dans les grandes lignes. Poverty? Personnellement, j'aime beaucoup cette technologie, elle est, et de loin, ma nouveaut prfre du Framework .Net 3.0. A Best Friend Essay? WCF vient point nomm, au moment ou les technologies d'applications distribues taient trop nombreuses et varies, et aussi au moment o les besoins en interoprabilits sont croissants. English Essay Place? Cet article constitue une introduction WCF, et il faut le prendre en tant que tel. Friend Essay? WCF est une technologie trs large et qui peut tre complexe, c'est pour cette raison que cet article n'est que le premier d'une srie.

Je vous invite donc consulter le site frquemment, d'autres articles sur WCF suivront dans les semaines venir. Un grand merci AGM26 pour la relecture de cet article, ainsi qu' l'quipe Dotnet pour son aide. Vous avez aim ce tutoriel ? Alors partagez-le en cliquant sur les boutons suivants : Copyright 2007 Ronald Vasseur. Composition Paper? Aucune reproduction, même partielle, ne peut être faite de ce site et de l'ensemble de son contenu : textes, documents, images, etc. A Best Friend Essay? sans l'autorisation expresse de l'auteur. Deprivation Essay Conclusion? Sinon vous encourez selon la loi jusqu'à trois ans de prison et jusqu'à 300 000 € de dommages et intérêts.

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Best Friend ( descriptive writing of a friend) essays

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Check a minimalist PSD solution with an elegant black and white palette, smart content organization, and icons for easier comprehension of the a best friend essay, info. Here is a well-crafted resume template designed in the Infographic style and available in the PSD format for easy customization. 6 Professional Resume CV Templates. This package contains 6 professionally designed CV templates. Each of them includes a two-page resume and sleep essay conclusion one cover letter. To customize the templates, simply insert your photo and friend essay replace the default text with yours. Conclusion? Curriculum Vitae for friend, a Graphic Designer.

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This AI vector file features 8.5” x 11” dimensions, 300-dpi resolution, and CMYK color profile. Free PSD Resume Cover Letter Template. Photographers, designers, or any other artistic individuals are advised to consider this PSD package. It gives a free access to both a resume and cover letter. The freebie is notable for 3 color options, minimalist icons, and describe friend transparent background where you can add your photo or any other image. Essay? Take a look at another CV template to impress potential employers. Available in the AI format, it features ample white space spiced up with green accents and geometric shapes for an edgy look.

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Its main properties are as follows: AI format, 300 dpi, CMYK , unlimited resolution as well as editable colors, fonts and icons. To make the most of this freebie, use a step-by-step PDF guide available in its package. Smart Freebie Word Resume Template – The Minimalist. The next resume freebie has a minimalist yet content-rich design. It will help you reveal your candidacy in full to employees. The template is available in the .doc format, which means you’ll find it easy to describe a best friend customize it. Check out a bundle packed with 12 resume templates, 12 cover letters, and a creative portfolio template. There are also 30 hobbies icons, 50+ social media icons, and vector world maps. You can choose from Word and Indesign file versions.

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Best Friend ( descriptive writing of a friend) essays

EGAL - Essay Grading and Analysis Logic. The Project can be accessed online at http://egal.sourceforge.net. Developers : Ajit Datar, Nagendra Doddapaneni, Sudip Khanna, Varsha Kodali and Archna Yadav. INTRODUCTION TO AUTOMATIC ESSAY GRADING. As it is said, the three R's of a best friend, education are Reading, wRiting and aRithmetic. As a part of the same, writing has always formed an important part of poverty writing, education, either while being imparted or being evaluated. A Best Friend? As automation has become the order of the day, with most of the jobs being automated, evaluating essays has been an issue for long time. Since late 1960s, systems have been developed to place evaluate essays automatically. One of the early systems developed to address the describe a best issue at english describing hand was Project Essay Grader(PEG)[1].

This system was not accepted widely, because of the fact that most of the a best friend factors that this system considered were indirect, like number of commas, number of prepositions and number of uncommon words. The idea behind using such measures was intrinsic and hence was not widely accepted. After PEG, in the 1980s there was an grade essay evaluation system called Writer's Work Bench tool(WWB) which helped giving feedback for writers about various aspects such as spelling, diction and readability. The system had functionalities to support spell check and to point out a best often misused words. But because WWB did not take care of english describing place, semantic analysis, it was limited in describe friend scope - in terms of research paper, evaluation. During the same period Tom Landauer and his associates came up with an approach called Latent Semantic Analysis[13][20]. This Latent Semantic Analysis (LSA) based techniques use a ``bag of words'' approach, wherein the word order is not considered important, but similarity between words is and is measured using a co-occurrence matrix and singular value decomposition. Tom Landuer and his associates furthered research into the approach and developed the describe friend essay Intelligent Essay Assessor(IEA)[14] system. Now there was another system that followed PEG, namely E-RATER[15][16], a system developed at ETS.

It used more direct measures and has been used to grade essays written in the GMAT exam. The measures used by E-RATER are more comprehensive and include the document structure. Thus the students' response can be measured for similarity with a training set of essays and based on this similarity value, given a score on poverty writing essay, a point scale from 1-6, Later, in 1999 Christie architectured a new essay grading system SEAR (Schema Extract Analyse and Report)[17] which was based on a new parameter, the style of the essay rather than content. Essay? It required an freshman research paper initial training and calibration on a set of essays.

Also it had a reference content called the content schema which was represented as a data structure and can be flexibly revised as and when required. SEAR had inspired others to consider the style of the essay, though it had its pros and describe a best essay, cons. In the following year, three students Ming, Mikhailov and Kuan at NGEE ANN polytechnic came up with an essay grading system called Intelligent Essay Marking Systems (IEMS)[18], which was based on the Pattern Indexing Neural Network(Indextron), a clustering algorithm that can be implemented over freshman composition paper, a neural network. IEMS was accoladed for a best friend essay its instant feedback to the student in a way by which students can learn where they had performed well and also the specifics of their mistakes. After three years of research and development, Mitchell, Russel, Broomhead, and Aldridge in 2002 came up with a software called Automark[19] intended for marking answers to outlines paper open-ended questions. It is based on the NLP methods and describe, incorporates methods for spell checking, semantic checking and support for freshman composition paper punctuation checking. It looks for specific content in the free-text answers. Content is in the form of templates which indicate correct or incorrect answers. Another step in the direction of automatic text assessment. In our system, there are four areas we are considering for the evaluation of an essay.

They are Gibberish Detection, Irrelevance Measure, Identifying Statements of describe a best friend, Fact and Checking statements of deprivation essay, fact for their accuracy. Let us discuss each of these modules one after the other. To start off, there can be two types of gibberish sentences. Syntactic gibberish sentences and semantic gibberish sentences. A sentence is considered to be syntactic gibberish if it is so ungrammatical that it does not make any sense. So a syntactically gibberish sentence is just not ungrammatical, it is describe essay, so highly ungrammatical that the it is equivocal.

Let us consider the following sentence ``I go the on overcoming fear of public speaking market.'' It is ungrammatical, since the preposition ``to'' is missing in the sentence. Even though this sentence is describe a best essay, ungrammatical, we can still understand whats is being said. Now consider the sentence ``At flying no market ran.'' This too is ungrammatical but it does not make any sense. Hence, it is considered to be syntactic gibberish. Now let us consider what semantic gibberish sentences are. Sleep Deprivation Essay Conclusion? A sentence like ``Colorless green ideas sleep furiously'' is considered semantically gibberish. Such sentences are grammatical but do not have any meaning. The more the number of gibberish sentences the less the student demonstrates command over written English, especially when writing in response to a prompt/topic.

Moving over to the next measure, we use an friend essay irrelevance measure to say if a sentence is relevant to the given topic or not. English Describing Place? Given a topic/prompt for the essay, a sentence from the student's response is considered to a best be irrelevant if the sentence does not relate to the topic. Now to say automatically that a sentence does or does not relate to grade 10 canadian history the topic, we compute the semantic similarity of the sentence with topic text. A Best Friend? We use WordNet to find this similarity. This means that the student can use a completely different set of words to talk about the topic and still be considered relevant. Research Paper? For example say the prompt asks the student to write about the ``Importance of class room teaching versus learning from a best essay, home'' and the student writes ``Education is very important for english describing place one to succeed in life.'' This is considered to be relevant, because the describe friend essay words 'education', 'teaching' and 'learning' are semantically close to paper each other. Now if the a best essay student responds by writing ``The sun is the biggest star in the universe'', then the sentence is irrelevant, because it does not talk about the topic. The more the number of irrelevant sentences the less the student shows an understanding of the essay fear of public topic. The next measure is to identify statements of fact from a student's response to an essay topic. A sentence is describe a best friend, considered to be a fact against an opinion, if the grade 10 canadian questions following four properties hold good (i) Information presented Unique and One of a kind (ii) Information presented Concrete (iii) Information presented a Statement or Proposition and (iv) Information presented an association between more than one concept[2] So if the sentence contains such information, we can identify the statement to describe friend essay be a fact.

Now if on the other hand, one considers personal statements then they are not concrete and hence cannot be facts. Such personal statements would be opinions. Thus the statements of fact would be identified against statements of opinion. Also questions and describing place, imperative statements form a category apart from statements of fact. If a sentence contains comparative adjectives like 'smarter' or superlative adjectives like 'smartest', or if the friend sentence contains comparative adverbs like 'faster' or superlative adverbs like 'fastest' then the sentence is not a statement of essay fear speaking, fact, because such a sentence would not be concrete. Also, sentences about future are not a proposition, as there is an element of uncertainty related with future, and describe a best friend essay, hence such sentences cannot be statements of fact. Let us consider an example. If the topic was the outlines paper same as given in the previous section about describe a best, teaching, and if the research paper student response was ``Learning from home started in describe a best friend essay USA from 1965'' is considered to essay be a statement of fact, irrespective of a best, whether the statement is sleep essay, relevant or not. The statement contains information which is unique(1965), concrete ('something starting'), and has no words that can be interpreted in more than one way in different contexts. Now if there was a sentence like ``Learning in class rooms is good'', it is not a statement of fact, but a statement of opinion, because what seems to be 'good' to one person, might not be the same for essay another.

Thus personal statements cannot be considered as statements of fact. Thus the freshman research paper more such facts are stated, the better we evaluate what the describe essay student envisions about the topic at hand, by relating the topic with concrete statements i.e. facts. The final measure to be used for evaluating essays is evaluating statements of fact for accuracy. Now that we have identified the statements of fact, we check to see if those facts are accurate and if they are, they contribute to a boost in the score. Writing Essay? Let us consider the describe a best friend topic from the last measure about learning. Essay? If the student writes ``Class room teaching started in 1965 in the USA'' and say in describe friend fact that it started in grade 10 canadian questions 2000. Then although the statement is a fact, it is a best friend essay, not accurate. Thus inaccurate facts contribute inversely to the score, while accurate facts contribute positively to research paper the score.

IMPLEMENTATION OF BASELINE APPROACH. The four measures implemented are Gibberish Detection, Irrelevance Measurement, Identifying statements of fact and describe a best essay, checking for Accuracy of Statements of Fact. The best results would be when we run each of the deprivation essay modules in a best essay the above order, so that for sleep conclusion each phase we get sentences that are more appropriate to check i.e. if a sentence is gibberish, then there is no point in checking to see if it is relevant or not, and if a sentence is irrelevant then there is no point in checking to see if it is friend essay, a statement of fact or not. Let us look at essay on overcoming fear the implementation of each of the four modules - The EGAL::Gibberish module implements Gibberish Detection. The method implemented is.

isGibberish() - This method determines if a given sentence is describe a best friend essay, gibberish or not. It first checks to see if a sentence is semantic gibberish or not as follows - The module first strips off the stop words from the essay describing place sentence. The remaining content-bearing words are stemmed using the stemmer provided along with Lingua::EN::Tagger. Stop words refer to a list of describe a best essay, function words, that contribute to the grammar alone and english describing place, not to the meaning of the sentence. If there are at least three content-bearing words in the sentence, then for describe friend all such words, using similarity metrics described later, we compute how similar each word is to every other word. Thus if we have N words in the sentence, we end up with a NxN matrix. Then we compute the average of all the entries in the matrix to research determine the semantic coherence of the sentence, a value between 0 and describe, 1. The compliment of essay fear of public speaking, this value scaled between 0 and 100 is the a best percentage gibberishness of the sentence. Writing Essay? If the scaled score is above an empirically decided threshold of 90%, then the sentence is flagged as semantic gibberish. Let us consider the sentence ``There is on the list fish and meat that are eating each other''. The only content-bearing words in this sentence are 'eating', 'meat' and 'list'.

The semantic similarities between these words are eating-meat - 0.1581 eating-list - 0 meat-list - 0. This gives us a value of 0.0527 for the semantic coherence of this sentence. Percentage gibberishness is calculated as (1-0.0527)*100, i.e. 95.73% which is above the threshold of 90% and hence we flag this sentence as semantic gibberish.The threshold we have used has been experimentally derived. After working on a list of sentences which were assessed by humans as gibberish/non-gibberish, the system was tuned to be consistent with the aforementioned judgments, by describe friend essay, setting the threshold accordingly. To compute the similarity between words, we used WordNet::Similarity::wup. The measure has been used for words found in conclusion WordNet. For those words not found in the knowledge base, a similarity value of 0 is used, which results in a reduction of semantic coherence and describe a best friend, therefore an increase in gibberishness, which is complimentary to semantic coherence. We POS tagged the poverty sentence using Lingua::EN::Tagger to identify the part of speech of friend, every word in the sentence. While computing the similarity between sentences, we considered all the senses of a word, given the part of speech that was used in the sentence. Now as we know the part of speech of a word, we would be able to distinguish the sense of the word ``I'' as used in sleep deprivation the sentence ``I am going there.'', where ``I'' would be a pronoun and as in a sentence like ``The element I is found in a best the periodic table'', where ``I'' would be a noun, as in Iodine.

This would enable us to handle some of the surprising words found in WordNet, based on the part of fear, speech of that word in the sentence. If the a best sentence is below the threshold (not semantic gibberish) then we check to see if it is syntactic gibberish. To determine if a sentence is syntactic gibberish, we do the grade history essay questions following - If the percentage of unknown words and unused links (score) in describe friend the sentence is more than an empirical threshold then we say that this sentence is syntactic gibberish. The threshold has been experimentally found to work best at a value of 50%. A syntactic gibberish sentence would have lot of unused links according to Lingua::LinkParser, a grammar parser used to parse sentences. Based on this, if the score is 0 then the sentence is grammatical. If it is a relatively small value it is essay on overcoming of public speaking, ungrammatical but not gibberish and if it is high, then the sentence is describe, considered to be syntactic gibberish. Sleep Deprivation Conclusion? This method takes in a sentence from the essay students response for a topic as input and returns an array, with the zero index contains a 1 if the sentence is gibberish and a 0 otherwise. At index 1, the array contains the gibberish score associated with the sentence and at 10 canadian essay index 2, the array contains detailed trace of execution. The alpha version for the module started with identifying only syntactically gibberish sentences.

To flag a sentence as syntactic gibberish, we considered an absolute value of the describe number of unknown words and of public speaking, unused links. If that value was greater than 3 then we termed the sentence as gibberish. Describe Friend Essay? But this value of 3 remained as threshold be it a sentence of length 5 or length 25. For the beta version, the module was able to identify semantically gibberish sentences as described above. An improvement over beta version, has been achieved in the final version, with modification of the absolute threshold for paper syntactic gibberish sentences. The threshold has now been converted to a percentage of unknown words/unused links. Thus if such words/links are 3 out of 5, then as this percentage is 60%, we flag the sentence as syntactic gibberish. If such words/links are 3 out of 25, then as this percentage is 12%, we do not flag this sentence as syntactic gibberish, even if there were 3 such words/links.

isIrrelevant() - This method takes in a sentence from the friend students' response as input. It then computes the relevance of the sentence with the topic/prompt. We consider the writing essay content-bearing words to contribute to friend the relevance of a sentence. Now we consider each of the content-bearing words from the input sentence and we compare each such word with every word in the topic. So for every word in english place the topic, we find the maximum similarity that such a word has with any word in describe a best the input sentence, using WordNet::Similarity::wup. We then compute the average over outlines research paper, all such maximum similarities for each word in the topic. The compliment of this value scaled between 0 and 100 is the percentage irrelevance of the sentence. If this score is above an empirically decided threshold then the sentence is considered to be irrelevant. After experimenting with sample responses for topics/prompts, we have decided on a threshold of 70%.

With such a threshold most of the friend essay sentences that a human assessor would evaluate as irrelevant are being detected as irrelevant. This method returns an array with its zero index returning a 2 if the grade 10 canadian history essay questions sentence is irrelevant and a 0 otherwise. The array index 1 contains the irrelevant score between 0 and 100. The array index 2 contains the detailed execution trace. The alpha version for the module started with comparing words from the a best essay student's response to words in freshman research the topic and ``gold standard essay''. This list of ``gold standard essays'' have been written by describe a best essay, an expert in the field, for every possible essay topic that the system would handle.

This word match also considered synonymous words by using Thesaurus.com, but the module was still looking for word match, which is not necessarily a semantic match. Thus for the beta version, the poverty writing module found the semantic similarity between a sentence from student's essay and the topic, by using WordNet::Similarity::wup. Thus the problem of maintaining ``Gold Standard Essay''s has also been eliminated. A Best? The performance of the module has been found to be satisfactory and hence has been retained for 10 canadian the final version. The EGAL::FactIdent module implements the Identification of Statements of Fact.

The methods implemented are. fill_stop_hash - this method fills a hash with value words that say that a sentence containing such words is an opinion, not a fact. fill_fact_hash - this method fills a hash with fact words that say that a sentence containing such words is a fact. which are called as a part of the constructor. isFact - this method takes in a sentence from the describe students response for freshman composition research paper a topic/prompt. Describe Friend Essay? It first checks to see if the sentence contains a comparative adjective like 'smarter' or a superlative adjective like 'smartest' or a comparative adverb like 'higher' or a superlative adverb like 'highest'. English Describing Place? If the sentence contains such a word, then it is identified not to be a statement of fact. Next it is checked to see if the sentence is in any form of future tense. If it is, then the sentence is identified not to be a statement of fact. Then it is checked to see if the sentence is a question and if it is then it is not a statement, let alone a statement of describe friend, fact. Then it is checked to see if this sentence contains value words or fact words.

If it contains such words, then the sentence is identified to be a statement of opinion or statement of fact respectively. Now, that if a sentence contains value words, it makes it a statement of research paper, opinion, was given by John Langan[6] in describe a best a discussion about distinguishing facts from opinions. Now we obtained a list of such value words from a project that worked on identifying such value words[7]. The list of value words and fact words have been put up on describing, links [21] and [22] respectively. Also if the statement contains statistics then it is identified to be a statement of fact.

Finally as we identify statements of fact using elimination, all others sentences which do not qualify for any of the other conditions would be treated as statements of fact. This module also returns an array with index zero returning a 4 if the sentence is a statement of fact and a 0 otherwise. At index 1, the array returns always returns a 0 as there is no concept of a score associated with identifying statements of fact and at index 2 the array returns a message indicating if the sentence is a statement of fact or not. If not, the describe a best reason as to why the sentence is not a statement of fact is on overcoming, sent here. The alpha version for the module started with identifying value words in sentences. Such sentences with value words are identified to be statements of opinion.

If sentences contained fact words then the sentence has been identified as statement of fact. Also if a sentence contained statistics then again the sentence has been identified as statement of fact. For the beta version, we have identified sentences with comparative/superlative adjectives/adverbs not to describe be statements of fact. Also sentences in future tense have been identified not to be statements of fact. The module has been found to work satisfactorily and hence has been retained for final version. The EGAL::FactCheck module checks the statements of facts for accuracy. The method implemented is. check_fact() - This method takes in a sentence from the students response to a prompt/topic. Essay Speaking? A linkParser[4] tree for the above sentence is built. Describe Friend? Using regular expressions the subjects for all the deprivation verbs is identified.

A Google query is a best friend essay, then constructed to search en.wikipedia.org [3] using the subjects and any proper nouns in the sentence. If there are no proper nouns, all noun phrases are used. The first Google result is taken and full text associated with this Wikipedia entry is retrieved. We then calculate the frequencies of all the n-grams in the sentence as observed in the full text. Writing? We have considered n-grams of at most length 3. and applied Witten-Bell smoothing to describe the obtained frequency list. A confidence measure is essay, calculated for each sentence. The measure takes in some arguments that we shall now see. 'n' refers to describe friend the number of conclusion, words in the n-gram. 'count' refers to the number of times the a best friend essay n-gram has occurred in the wikitext/sentence. History Essay? 'N' refers to the maximum n-gram length considered which is in our case is 3. Thus based on whether the count is positive or negative, we add or subtract n*(log(count) + N) respectively to describe a best the 'measure'. This is done for each of the n-grams in the sentence. Also if count is positive an accumulated score of n*(log(count) + N) is made to 'max' and to 'min' otherwise. We compute the final 'score' as score = (measure - min) * 100 / (max - min) This score represents the confidence, expressed as a percentage, with which we say that a particular statement of place, fact is accurate. The module started with the beta version for the project.

The module has been found to work satisfactorily, except for a best return status of outlines research paper, facts. The verbosity of the return message has been enhanced to display more information in the log files. With this modification, the module was ready for the final version. Following is a best friend, a list of tasks and group member who worked on the same - Gibberish Detection - Sudip Khanna and Ajit Datar. Irrelevance Measure - Sudip Khanna. Identifying Statements of Fact - Nagendra Doddapaneni.

Checking Accuracy of Statements of essay conclusion, Fact - Ajit Datar and friend essay, Sudip Khanna. Web-Interface - Archana Yadav and writing, Ajit Datar. Installation and Administration - Ajit Datar. Documentation - Nagendra Doddapaneni and Varsha Kodali. Literary Review - Nagendra Doddapaneni and Varsha Kodali. Irrelevance Measure - EGAL::Relevance identifies sentences to be relevant based on similarity score calculated using WordNet::Similarity::wup. If the percentage irrelevance is More than a threshold then the sentence is considered to be irrelevant and relevant otherwise. Identifying Statements of Fact - EGAL::FactIdent identifies sentences to be statements of describe friend, fact or not based on the occurrence of fact words and composition research paper, stop words respectively.

If value words occur in a sentence from the a best friend essay student's response, then the sentence is considered to be an opinion, because value words are mostly used to express personal view. If fact words such as ``first'' occur in the student's response or a number occurs in the sentence which is not gibberish and is relevant, then the sentence is considered to be a statement of fact. Also questions are not statements themselves and hence are not statements of fact. Even sentences with comparative/superlative adjectives/adverbs are not considered be statements of outlines research paper, fact as they are not concrete. Also if the sentence is in any form of future tense then again the sentence is not a statement of fact as it not a proposition. Checking Statement of Fact for Accuracy - EGAL::FactCheck determines the accuracy of the a best friend statements of facts. As mentioned before this module first constructs a LinkParser tree for the sentence from the student response to a prompt and identifies the subject using regular expressions. Essay On Overcoming Of Public Speaking? Then a Google query is constructed and fired to en.wikipedia.org using the subject and proper nouns/noun phrases. Describe A Best? Using the first Google result, fulltext for essay on overcoming fear this Wikipedia record is retrieved.

Now to check the accuracy of the statement, we develop a score based on the statistics obtained from friend essay, considering all n-grams from the sentence and applying Witten-Bell smoothing to the frequency of such n-grams as observed in the wikitext. Presently n-grams of length upto 3 are being considered. Thus using this score, we can say that the given statement is outlines research paper, a statement of fact with score% confidence. The four modules that we have implemented, give us details of the percentage of gibberish sentences, irrelevant sentences and statements of fact, along with their accuracy. With this information in hand, to develop a scoring mechanism consistent with as scored by a humam grader, would be difficult. Thus we came up with a measure with uses maximum information that can be derived from what statistics the modules offer. The scoring mechanism that we are using, is a two-phase scoring mechanism. During the initial phase, we consider two bins of sentences. A bin of good sentences which contain statements of fact and ordinary sentences. A bin of bad sentences which contain gibberish sentences and a best, irrelevant sentences.

We compute the total percentage of freshman composition research paper, sentences from the a best essay essay, that go into each of the two bins. Composition Research Paper? For example, if the essay had 10% sentences which are gibberish, 20% sentences are irrelevant, 30% sentences are statements of fact and the remaining 40% sentences are ordinary sentences. Then the total percentage of sentences in the good bin is 70%, while the total percentage of essay, sentences in composition research the bad bin is 30%. Describe A Best? Then if the good bin has higher percentage sentences than the bad bin, as is the case, then we consider the score of the essay to be either 3, 4, 5 or 6. The higher the composition research percentage of sentences in the good bin, the higher would be the score. For the given example, a score of say 4 is assigned. Now, if there were higher percentage sentences in the bad bin, then a score of either 0, 1, 2 or 3 would be assigned. Thus the initial phase scoring mechanism assigns an integral score to the essay. Now, the describe a best friend final phase scoring mechanism, considers all the statements of fact. It computes the mean of the confidence levels associated with each of the statements of essay, fact.

If the mean is greater than 50, then the describe friend score assigned by the intial phase scoring mechanism, is incremented by a fraction. If the mean is essay, less than 50, then instead of a score boost, the a best friend score would be penalised. By how much, is dependent on the confidence level of facts. Grade History Questions? For example, there were two statements of fact in the essay. One was verified with 62% confidence level and the other was verified with 78% confidence level. Then the friend essay mean of the confidence levels would be (62+78)/2 which is 70%.

Now, since this value is greater than the threshold of 50%, the score of 4, assigned by the initial phase scoring mechanism, is incremented by the final phase scoring mechanism. So say, a score boost of essay place, 0.6 is given. Then the final score would be the sum of the scores assigned by intial phase scoring mechanism and the boost given by the final phase scoring mechanism. So for the example that we considered, the final score would be 4.0 + 0.6 = 4.6 . Now this final value is rounded off to the nearest half number. So 4.6 is rounded off to 4.5 . In the final phase mechanism, the value for describe score boost has been identified to be following an conclusion exponential i.e. for friend essay a mean of on overcoming of public speaking, 60%, the boost to be given is less, while for describe a mean of 95%, the poverty boost to a best friend essay be given is much more. Thus an essay on overcoming fear speaking exponential function [((mean-50)*1.26)/50]^3 has been experimentally found to work well, for scoring the essays. As a part of evaluation, we have in place modules which check to see if a given sentence is gibberish, if not if its irrelevant and if not if its a statement of friend essay, fact and if it is then we check for its accuracy. Thus on running the system over the following input - The following are the sentences that have been successfully identified as gibberish by the EGAL::Gibberish module - Thus keeping the scores, assigned by each of the modules ,in view and their identification of sentences, in the respective categories, rightfully, the system has been able to achieve expected results. Following is a detailed run of the system, with details about some sample essays that the user has given for some prompts used in fear speaking the system.

Details about what sentences in each of the following essays have been identified as gibberish, irrelevant and statements of fact can be seen in the following text. The following is a response which was graded to be a 3 point essay. Our EGAL system graded the essay to a 3.49 score. This was for the prompt: The user response is : The next essay was evaluated to be a 4 pointer, and it was evaluated to be a 2.61. The essay topic was.

For a third essay, the EGAL system has graded the system to be a 4.0 pointer, where the essay was graded to friend be a 5.0 pointer. The topic of the essay was : The user response was : The fourth essay is a combination of two 3-point essays written by our co-students for a prompt given commonly in class. The EGAL system graded this grouped essay to poverty writing essay be a 3.62. The student response was. -------------------------------------------------- DETAILED DIAGNOSTICS OF THE ESSAY: -------------------------------------------------- Type of Sentences Identified Percentage Gibberish 17.39 Irrelevance 17.39 Facts 26.09 Ordinary 39.13 Percentage of friend essay, Gibberish Sentences were: 17.39 Percentage of Irrelevant Sentences were: 17.39 Percentage of Fact Sentences were: 26.09 Percentage of Ordinary Sentences were: 39.13 No. of Gibberish Sentences were: 4 No. of research, Irrelvant Sentences were: 4 No. of Facts Sentences were: 6 No. of a best essay, Ordinary Sentences were: 9 gibberish sentences were as follows Sentence Many students write essays for exam, some write good, some bad, some worst. Points 91.51% Semantic gibberish Sentence The compter cannot get this idea of good, bad, and worst. Points 63.64% Syntactic gibberish Sentence In this case the computer would just be too good to score and give good score to essay describing someone who cant even write a creative sentence nor can write grammatical correct sentece.

Points 92.21 Semantic gibberish Sentence Using computers makes work faster. Describe A Best Essay? Points 94.44% Semantic gibberish irrelevant sentences were as follows: Sentence Last but not least, computer scoring ethically is essay, not good. Friend Essay? Points 75.51% Sentence Automated essay scoring is used in GMAT and outlines research, GRE. Friend Essay? Points 72.83% Sentence If a good computer is used this difference can be reduced. Writing? Points 70.31% Sentence It just has some difference but not to a greater extent and describe a best essay, such deviations can be ignored as even humans make mistakes. Points 75.00% fact sentences were as follows: Sentence It just tries to find information the ways it is supposed to and scores that way. Points 40.23% I can say this is a fact with 40.23 percent confidence Sentence It uses computers to grade student essays. Points 0.00% I can say this is a fact with 0.00 percent confidence Sentence First of all, the difference between human graded essay and computer graded essay is not very significant. Points 22.31% I can say this is a fact with 22.31 percent confidence Sentence Both tend to be the same.

Points 14.48% I can say this is a fact with 14.48 percent confidence Sentence Even though each student has his own views the computer is intelligent enough to catch the differences and grade accordingly. Sleep Conclusion? Points 37.05% I can say this is a fact with 37.05 percent confidence Sentence Thus, the computer does not grade an essay harshly than humans. Points 13.05% I can say this is describe a best friend essay, a fact with 13.05 percent confidence ordinary sentences were as follows: Sentence Thts why automated essay scoring is unfair to students. Message This sentence is a statement of fact Nouns: ``thts'' Subjects: ``scoring '' Google query: ``scoring '' ``thts'' site:en.wikipedia.org System cannot verify this using the existing knowledge source. Sentence For examples, many student know that the computer checks the outlines research essays, therefore they learn how to describe a best essay ebat the machine rather then being creative to write their essays and learn something. Message This sentence is a statement of fact Nouns: ``checks'' ``ebat'' ``essays'' ``student'' ``computer'' ``machine'' ``examples'' ``something'' Subjects: ``''``examples '' Google query: ``''``examples '' ``checks'' ``ebat'' ``essays'' ``student'' ``computer'' ``machine'' ``examples'' ``something'' site:en.wikipedia.org System cannot verify this using the existing knowledge source. Sentence Another point here we can see is sleep essay, that the computer learns from essays written by students, now if the essay sample essays are not that creative then if someone writes creative essay it will just get confused and give some random score, if not then it will give the best possible score which is still not correct. Message This sentence has comparitive/superlative adverbs/adjectives Sentence So is it fair to get garbage or grate score from machine?

Message This sentence is a statement of fact Nouns: ``score'' ``grate'' ``garbage'' ``machine'' Subjects: Google query: ``score'' ``grate'' ``garbage'' ``machine'' site:en.wikipedia.org System cannot verify this using the existing knowledge source. Sentence To conclude I would say stop this computer scoring, it doesnt make sense when you write an essay thinking hard and someobody who is not real grades it for you and gives you something that you dont confidence about. Message This sentence is in future tense Sentence It also reduces the work load on human graders. Message This sentence contains the value word work Sentence As a student writes an essay the computer can understand how the student writes and outlines paper, this will help it in grading. Message This sentence is in future tense Sentence Finally, I feel that the usage of a best friend, automated essay scoring is good and should be followed by all including schools and essay, universities.

Message This sentence is in future tense Sentence It will help students and teachers a lot. Message This sentence is in a best friend essay future tense. The fifth essay sample that we are looking at is the topic/prompt given as the response for a topic/prompt. The EGAL system has evaluated such a tricky response to a score of 1.96. The topic/prompt was. The response was entered to be. This would usually trick a system, as the response seems to freshman research be pseudo-relevant. A Best? But here is the freshman research paper analysis of describe, how EGAL handles the same- Now for the sixth essay, we considered a 6 point esssay which was graded as 4.99 on freshman composition paper, our EGAL system. The essay topic was : The user response was: Now for the seventh essay, we considered the same 6-point essay for the trvious topic, and evaluated it for a different topic.

The EGAL system graded the essay to be a 2.99 score essay. The response was the same as the describe a best essay one for the last one. There are some systems that we would like to acknowledge, since we used them as a part of our system. For Gibberish Detection, we used Link Grammar, a grammar parser[4]. This parser enables us to find unused links and unknown words in a sentence. With the help of this parser, we were able to identify syntactic gibberish. We have used WordNet::Similarity package, built on WordNet2.0[10] for freshman composition research finding the semantic similarity between two words. This is used in identifying semantic gibberish as well as relevance of a sentence to the topic. For identifying statements of fact, we used ideas from online resources [2], [6], [7] and describe friend essay, [8]. Essay? Each of a best friend essay, these references have helped us decide the basis on which to distinguish facts from opinions and also to identify the properties of a statement of fact.

To check for the accuracy of these statements of facts, we use the idea of a fact repository from Static Knowledge Sources[9], which would be wikipedia.org[3] in our case. We access this online encyclopedia by constructing a Google query using Google API[11] and fire the query to retrieve wikitext for the first match found by Google in en.wikipedia.org. [1] Page, E.B. Conclusion? , 1994, New Computer grading of student prose, using modern concepts and software, Journal of Experimental Education. [5] Peter W. Foltz, Darrell Laham, Thomas K. Landauer, The Intelligent Essay Assessor: Applications to Educational Technology, http://imej.wfu.edu/articles/1999/2/04/index.asp. [7] Human Value Project, http://www.uia.org/values/vztab12.htm, Union of International Associations 1997 - 2004. [9] The Static Knowledge Sources: Ontology, Fact Repository and Lexicons, http://ilit.umbc.edu/Book/sks.htm. [10] WordNet 2.0, ``A lexical database for the English language'', http://www.cogsci.princeton.edu/ [12] Valentini, Salvatore, Francesca Neri, and Alessandro Cucchiarelli. 2003. An Overview of a best, Current Research on Automated Essay Grading.

In JITE, Vol-2,2003. [13] Deerwester, S.C., Dumais, S.T., Landauer, T.K., Furnas, G.W., and Harshman R.A. English Essay Place? , 1990, Indexing by Latent Semantic Analysis. Journal of the American Society for Information Science. [14] Hearst, M., 2000, The debate on automated essay grading. IEEE Intelligent Systems. [15] Burstein, J., Kukich, K., Wolff, S., Chi, L., and Chodorow M., 1998, Enriching automated essay scoring using discourse marking.

Proceedings of the a best essay Workshop on Discourse Relations and Discourse Marking, Annual Meeting of the Association of Computational Linguistics, Montreal, Canada. [16] Burstein, J., Leacock, C., and Swartz, R. , 2001, Automated evaluation of essay and short answers. 10 Canadian History? Proceedings of the Sixth International Computer Assisted Assessment Conference, Loughborough University, Loughborough, UK. [17] Christie, J.R., 1999, Automated essay marking-for both style and content. Essay? Proceedings of the Third Annual Computer Assisted Assessment Conference, Loughborough University, Loughborough, UK.

[18] Ming, P.Y., Mikhailov, A.A., and Kuan, T.L., 2000, Intelligent essay marking system. Learners Togeather, Feb 2000, NgccANN Polytechnic, Singapore http://ipdweb.np.edu.sg/lt/feb00/intelligent_essay_marking.pdf IEMS. [19] Mitchell, T., Russel, T., Broomhead, P., and Aldridge N.(2002) . Towards robust computerized marking of free-text responses. Proceedings of the Sixth International Computer Assisted Assessment Conference, Loughborough University, Loughborough, UK.

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Describe a Best Friend Essay

counter book reports Counting on COUNTER: The Current State of E-Resource Usage Data in Libraries. Once the internet became the ubiquitous way to access content, it did not take long for the library community to create standards to ease the process of collecting usage data. In 2002, librarians formed Project COUNTER (Counting Online Usage of Networked Electronic Resources). A year later, COUNTER issued Release 1 of its Code of Practice, which outlined standards for publishers and vendors to report usage statistics. In 2007, the information science standards body NISO (National Information Standards Organization) created the Standardized Usage Statistics Harvesting Initiative protocol, known casually as SUSHI, which provides an automated way to download COUNTER reports via the web.

While COUNTER and essay, SUSHI have helped libraries come a long way toward improving the adoption and availability of usage statistics for library market vendors, I soon came to learn that there is still a good amount of work libraries must do to get the data they need to make critical collection development and research paper, database budgeting decisions. I learned my lesson the hard way, by first turning to SUSHI with the hope it would fulfill my library’s need for data about database usage. Let me start at a best friend the start In early 2012, Southwest Baptist University (SBU) Libraries began the essay, daunting task of collecting electronic resource usage statistics. As the describe essay, new electronic resources librarian, I got the job, which I immediately attempted to systematize and essay conclusion, hopefully simplify. SBU did not have the funds to a best, acquire a commercial electronic resource management (ERM) system, so after much difficulty, I built a functioning SUSHI harvester based on Python and MySQL. To make a long story short, details, instructions, and source code for this project can be found on my blog at http://josh-welker.blogspot.com . The bottom line was that building a working SUSHI client may not have even been necessary, but it certainly was not sufficient. Sleep Deprivation Conclusion! In order to describe friend, fully evaluate usage, I needed to composition paper, conduct a standard cost-per-use analysis of SBU’s electronic resources. Cost-per-use studies require two simple data ingredients: cost and usage. A Best Friend Essay! Cost was easy enough to find, but usage proved impossible to place, measure with SUSHI for most vendors. The only a best friend COUNTER report available via SUSHI that measures full-text uses is the JR1 report, which counts uses per journal title.

But since the SUSHI standard does not allow librarians to history essay questions, specify a particular database, the JR1 report contains all the journals the describe friend, library can access from a vendor’s platform. SBU might subscribe to 2 dozen databases from a vendor, each with its own price tag. There is no way to calculate cost per use for those dozens of on overcoming fear of public, databases when a vendor lumps all the usage figures together into one report. So at the end of the day and after all my work building a SUSHI client, I still ended up having to visit dozens of vendor websites to manually collect, collate, format, and analyze all the data myself, using the classic desktop applications Access and describe, Excel. A Study of Electronic Resource Statistics in Libraries. After becoming thoroughly disillusioned with SUSHI, I wanted to know if I was alone or if other libraries were bogged down in the same statistical quagmire. The rest of this article is about the results of a survey I conducted among my peers to poverty, not only satisfy my own curiosity but with the hope that such a study would reveal insights that the vendor community and COUNTER/NISO could use to a best friend essay, improve the standards and protocols for collecting and reporting usage statistics. My short survey was assembled using SurveyMonkey and distributed through the LITA, ERIL, and Code4Lib listservs.

The survey contained four quantitative questions and two qualitative questions related to history essay questions, how libraries collect and use statistics. The survey was left open for 3 weeks. The results showed that SBU is not unique in experiencing difficulty with usage statistics. A total of 131 librarians responded to a best, the survey. Not every respondent answered every question. Anonymous raw data can be found on grade 10 canadian essay, my blog. I will summarize the a best friend, highlights here. The first question asked what methods libraries use to collect usage statistics.

Most librarians in the survey indicated that they manually collect usage data, just as I ended up doing in my project. SUSHI is research paper seldom used, which is describe friend essay unsurprising since vendor implementation is poor and ERM software is deprivation essay conclusion expensive and unwieldy. A Best Friend! Respondents did indicate that vendor websites provided COUNTER statistics more often than not, but a large number of vendors still provide no COUNTER statistics. The second question asked how much time librarians spend collecting usage statistics for each year. Research Paper! Responses were across the board, indicating significant variance between institutions. This variance is most likely due to factors such as the amount of electronic resources, available staff, and automation tools. As an electronic resources librarian, I view 1 week as an acceptable amount of time to spend collecting usage statistics. Friend! Only 23.9% of grade 10 canadian history questions, respondents indicated that they spend 1 week or less collecting statistics, whereas 40.7% of a best, respondents indicated that the process takes them 4 weeks or longer. The third question asked what kinds of data librarians find useful. Answers are mapped to a Likert scale with the following values: Not useful (0), Somewhat useful (1), Very useful (2).

The average response value was calculated for each category, ranging from 0 to 2. The highest scorers were Full-text Retrievals by Journal/Book (1.71), Full-text Retrievals by Database/Collection (1.69), and Searches by Database/Collection (1.50) by a margin of 0.33. This indicates that full-text retrievals are the main metric librarians care to know. Respondents ranked session and turnaway data unfavorably in general. It is also notable that the outlines, librarians in describe essay this survey did not care about on overcoming speaking platform-specific data, whether for full-text retrievals, searches, sessions, or turnaways. The fourth question asked which COUNTER reports are useful to describe a best, librarians. Answers were mapped to the same Likert scale as for the third question.

The highest-ranking COUNTER reports (see table on sleep deprivation essay conclusion, page 8) were JR1 (1.77), DB1 (1.55), and BR1 (1.47) by a margin of describe essay, 0.40. The popularity of JR1 and paper, BR1 is not surprising since these librarians indicated that they primarily care about the number of full-text retrievals. DB1 reports are very popular, even though they do not include full-text statistics, most likely because they are the only COUNTER report that gives any indication of use at the database level. All other reports scored between 0.75 and 1.05, indicating that most libraries find them only somewhat useful at describe friend best. The fifth question was qualitative and essay place, asked what major challenges librarians face when collecting usage statistics. Responses were grouped into describe friend, several categories as common themes emerged. By far, the biggest complaints revolve around vendor implementation. English Essay Describing! Of 175 respondents, 66 complained about vendor compliance and data consistency. Many vendors offer few or no COUNTER reports. A Best! The data is in a proprietary format that cannot be easily compared to other resources.

There is also no guarantee that vendors are counting usage the grade history essay questions, same way. Here is how one respondent described it: “for a search box that covers 5 databases and is searched 1,000 times in a month, [some vendors] will report 5,000 searches (1,000 for each database).” Librarians reported distrust of the vendors’ statistics. One said, “It strikes me that publishers and vendors don’t want us to see this data because some of it could cause cancellations.” Another mentioned having a “feeling that the describe a best essay, stats cannot altogether be trusted.” But the largest complaint, voiced by 71 respondents, was that collecting statistics is too tedious. In most cases, this is due to poor vendor interfaces. A common grievance was that smaller vendors have no web-based interface for collecting statistics and require that a representative be emailed to essay on overcoming fear of public speaking, ask for statistics. These contacts are often lost as libraries and vendors shuffle personnel. When vendors do provide an describe a best, online interface, there is still the issue of tracking down potentially hundreds of URLs and sleep conclusion, login credentials and learning every interface’s ins and outs. “There is no consistency,” one respondent wrote. “Each vendor’s site is different, and it takes a while to figure out a best friend, how to go about harvesting the use stats.” The extremely low implementation of SUSHI services exacerbates the problem.

Twelve respondents voiced frustration that vendors frequently change reporting platforms without notifying the right library personnel where and deprivation essay conclusion, how to use the new platform. Ten complained that it is too difficult to use the available metrics to friend, create a cost-per-use analysis; nine were frustrated that most vendors only report based on calendar year, while most libraries need data related to writing, their fiscal years. The sixth and final question asked what changes in the COUNTER standard would improve usage statistics. Fewer participants responded to this question (only 68 total), and responses were more varied. As in the previous question, responses were grouped by common themes. The most common suggestion, mentioned by describe a best essay 29 respondents, was requiring more uniform vendor implementation. One of the biggest problems in describing this regard is the a best friend essay, granularity of reporting. Grade History! Some vendors will include all journals in describe a best essay a JR1 report, whether the library subscribes to the journal or not. Research! Other vendors do not allow JR1 reports to target a specific database.

Vendors also commonly conflate platforms with individual databases, which prevents libraries from getting usage data for the individual products they buy. The second-most common suggestion is improvement of describe friend essay, automation tools. SUSHI is a great standard, but it lacks wide vendor implementation, and even more so, it lacks software tools that allow libraries to take advantage of it. Responses to the survey paint a somewhat bleak picture of the current landscape of electronic resource usage statistics. Librarians are spending inordinate amounts of time collecting statistics and are often not even able to get the information they need. As one respondent succinctly put it, there is “very little ROI in outlines terms of driving collection development decision-making given the amount of time that goes into gathering the data.” There seems to be a categorical misunderstanding among vendors regarding why libraries want usage statistics. Describe A Best! For the most part, librarians don’t care about sessions, searches, IP addresses, or page views. It’s all about cost per essay conclusion use. One respondent said, “[Cost per a best friend use] is the only bit of information that library administrators care about anyway.”

Vendors and COUNTER should do everything in outlines their power to make it easier for libraries to calculate cost per use. This includes providing full-text retrieval data for whatever the actual unit is that libraries are purchasing. If a library purchases a database, vendors should give usage data at the database level, not at the journal level or the platform level. This problem is especially rampant in SUSHI. NISO needs to include a parameter in describe essay the SUSHI specification that allows libraries to filter data by a specific database. Otherwise, the 10 canadian history essay, data is basically useless. The new COUNTER Release 4 updated the DB1 report to include result clicks and record views instead of just searches and a best, sessions, which is a great step in the right direction. However, at the time of writing, I could not find any vendors that had implemented the new DB1 report. How can we make this better? I’ve summarized my recommendations for vendors, standards bodies, and history questions, librarians in describe a best friend the box on the left.

Let’s work together to get better usage data easier. What Can We Do to deprivation essay, Get Better Usage Data? Here’s what vendors, standards bodies, and libraries can, should, and must do to improve electronic resource usage statistics: Invest in describe usability testing for essay fear speaking your administrator interfaces. At the bare minimum, look at your competitors’ reporting interfaces and describe a best friend essay, try to copy basic navigation elements. Do not require librarians to email you for usage statistics.

Make the stats available online. Periodically email librarians with the contact information of their current service rep, especially when your platform changes. Get on board with COUNTER. At the bare minimum, offer the JR1, DB1, and (if applicable) BR1 reports. If you sell databases, give reports at the database level. If you sell periodicals, give reports at sleep deprivation conclusion the title level. Do not think it is sufficient to give data at the platform level. Describe Essay! Realize that libraries need fiscal year data and allow libraries to input a custom time range for their usage reports. Standards Bodies (COUNTER and NISO) Focus on adding and updating COUNTER reports that measure full-text retrievals. Poverty Writing! For many libraries, this is the friend essay, only metric that matters.

Implement quality control measures to ensure that COUNTER-compliant vendors are giving accurate reports. Vendors should not be allowed to conflate platforms with databases in a DB1 report or to list journals a library does not have in a JR1 report. Consider sponsoring an open source SUSHI client that is clearly documented, easy to implement, and up-to-date with the current COUNTER release. Do not accept mediocrity from sleep deprivation, vendors. Let your service reps know that you are dissatisfied with the current reporting systems. Let them know you need SUSHI services.

Pay attention to a best essay, vendor reporting mechanisms and let them know when something is conclusion clearly broken. If a vendor calls itself COUNTER-compliant but clearly isn’t, contact Project COUNTER. Be willing to friend essay, educate yourself on and participate in NISO, Project COUNTER, and open source initiatives.