Language modeling information retrieval (11 Ergebnisse)
Information Retrieval Systems Supporting Arabic Language: Handling Multi Language Support For Information Retrieval System Using Modeling Design Methods, Word Analysis And Indexing Techniques
Alkhatib, Amr; Ashour, Soufian; Alkhatib, Tarek; Alkhatib, Amr; Ashour, Soufian; Alkhatib, Tarek
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Taschenbuch. Zustand: Neu. Neuware - This project designed to help performing sentences based search instead of matching keywords, results will be more accurate and similar to human comprehensive search result based.The project data based on Mysql database, written I Java programming language,based on number of IR libraries. The… system spitted in two project (distributed System) as follow. The indexer project: which parsing the Mysql database to be processed by the Analyzer (tokenizing ,filtering Steaming) then to store into an index file.The Searcher project which apply the input keyword to the same Analyzer applied for the indexer, then to be matched with the indexed file, then to return the matched data into Web-Pages.The IR system can return accurate search result that could ordered by percentage of relevant,thanks to using the Steamer module, by apply systematic roles on each word, to return it to its infinitive (grammatically),a new Steamer module was developed to support Arabic language ,which is still a developing topic in the area of IR Systems the project implements a full object oriented design using some advanced design theories such MVC (Model View Control and DAO (Data Access Object), multi tier design.
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Taschenbuch. Zustand: Neu. Information Retrieval Systems supporting Arabic language | Handling multi language support for information retrieval system using modeling design methods, word analysis and indexing techniques | Amr Alkhatib (u. a.) | Taschenbuch | 108 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 978365…9328947 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
Sprache: Englisch
Verlag: Springer, 2003
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Zustand: New. In.
Sprache: Englisch
Verlag: Springer, 2010
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Sprache: Englisch
Verlag: Springer Netherlands, 2010
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Zustand: New.
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Sprache: Englisch
Verlag: Springer Netherlands, 2003
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Zustand: New.
Sprache: Englisch
Verlag: Springer Netherlands, 2003
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Paperback. Zustand: Brand New. 264 pages. 9.00x6.00x0.59 inches. In Stock.
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Sprache: Englisch
Verlag: Springer, 2010
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - A statisticallanguage model, or more simply a language model, is a prob abilistic mechanism for generating text. Such adefinition is general enough to include an endless variety of schemes. However, a distinction should be made between generative mod…els, which can in principle be used to synthesize artificial text, and discriminative techniques to classify text into predefined cat egories. The first statisticallanguage modeler was Claude Shannon. In exploring the application of his newly founded theory of information to human language, Shannon considered language as a statistical source, and measured how weH simple n-gram models predicted or, equivalently, compressed natural text. To do this, he estimated the entropy of English through experiments with human subjects, and also estimated the cross-entropy of the n-gram models on natural 1 text. The ability of language models to be quantitatively evaluated in tbis way is one of their important virtues. Of course, estimating the true entropy of language is an elusive goal, aiming at many moving targets, since language is so varied and evolves so quickly. Yet fifty years after Shannon's study, language models remain, by all measures, far from the Shannon entropy liInit in terms of their predictive power. However, tbis has not kept them from being useful for a variety of text processing tasks, and moreover can be viewed as encouragement that there is still great room for improvement in statisticallanguage modeling.
Sprache: Englisch
Verlag: Kluwer Academic Publishers, 2003
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Zustand: New. Contains a collection of papers addressing developments in the design of information retrieval systems using language modeling techniques. This book is primarily for researchers and advanced graduate students working in the language technologies areas of computer science or information science. Editor(s): Croft, W.… Bruce; Lafferty, John. Series: The Information Retrieval Series. Num Pages: 246 pages, biography. BIC Classification: UN. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 15. Weight in Grams: 548. . 2003. Hardback. . . . . Books ship from the US and Ireland.
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Sprache: Englisch
Verlag: Springer Netherlands, Springer Netherlands, 2003
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - A statisticallanguage model, or more simply a language model, is a prob abilistic mechanism for generating text. Such adefinition is general enough to include an endless variety of schemes. However, a distinction should be made between generative models, wh…ich can in principle be used to synthesize artificial text, and discriminative techniques to classify text into predefined cat egories. The first statisticallanguage modeler was Claude Shannon. In exploring the application of his newly founded theory of information to human language, Shannon considered language as a statistical source, and measured how weH simple n-gram models predicted or, equivalently, compressed natural text. To do this, he estimated the entropy of English through experiments with human subjects, and also estimated the cross-entropy of the n-gram models on natural 1 text. The ability of language models to be quantitatively evaluated in tbis way is one of their important virtues. Of course, estimating the true entropy of language is an elusive goal, aiming at many moving targets, since language is so varied and evolves so quickly. Yet fifty years after Shannon's study, language models remain, by all measures, far from the Shannon entropy liInit in terms of their predictive power. However, tbis has not kept them from being useful for a variety of text processing tasks, and moreover can be viewed as encouragement that there is still great room for improvement in statisticallanguage modeling.








