Revision with unchanged content. Sentence Retrieval is the task of retrieving a relevant sentence in response to a query, a question, or a reference sentence. In this work we begin by demonstrating that because sentences are much smaller than documents, the performance of typical document retrieval systems on the retrieval of sentences is significantly worse. We propose several solutions to the problem of sentence retrieval, based on statistical translation models, and investigate these solutions the application areas of sentence retrieval for question answering, novelty detection, and information provenance. Statistical translation models are appropriate for tasks where the sentence to be retrieved benefits from the addition of related terms and synonyms. The context of a sentence affects its meaning, and smoothing from the local context of the sentence improves retrieval. A brief investigation of conditional models for sentence retrieval suggests conditional models outperform language modeling approaches, for some tasks. This book is addressed to students and professionals working on language technology systems that are dependent on sentence or passage retrieval.
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Postdoctoral Researcher for Yahoo! Research in Barcelona. PhD in Computer Science, University of Massachusetts at Amherst, Center for Intelligent Information Retrieval.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Revision with unchanged content. Sentence Retrieval is the task of retrieving a relevant sentence in response to a query, a question, or a reference sentence. In this work we begin by demonstrating that because sentences are much smaller than documents, the performance of typical document retrieval systems on the retrieval of sentences is significantly worse. We propose several solutions to the problem of sentence retrieval, based on statistical translation models, and investigate these solutions the application areas of sentence retrieval for question answering, novelty detection, and information provenance. Statistical trans lation models are appropriate for tasks where the sentence to be retrieved benefits from the addition of related terms and synonyms. The context of a sentence affects its meaning, and smoothing from the local context of the sentence improves retrieval. A brief investigation of conditional models for sentence retrieval suggests conditional models outperform language modeling approaches, for some tasks. This book is addressed to students and professionals working on language technology systems that are dependent on sentence or passage retrieval. 180 pp. Englisch. N° de réf. du vendeur 9783639453614
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Murdock VanessaPostdoctoral Researcher for Yahoo! Research in Barcelona. PhD in Computer Science, University of Massachusetts at Amherst, Center for Intelligent Information Retrieval.Revision with unchanged content. Sentence Retr. N° de réf. du vendeur 4989554
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Revision with unchanged content. Sentence Retrieval is the task of retrieving a relevant sentence in response to a query, a question, or a reference sentence. In this work we begin by demonstrating that because sentences are much smaller than documents, the performance of typical document retrieval systems on the retrieval of sentences is significantly worse. We propose several solutions to the problem of sentence retrieval, based on statistical translation models, and investigate these solutions the application areas of sentence retrieval for question answering, novelty detection, and information provenance. Statistical trans lation models are appropriate for tasks where the sentence to be retrieved benefits from the addition of related terms and synonyms. The context of a sentence affects its meaning, and smoothing from the local context of the sentence improves retrieval. A brief investigation of conditional models for sentence retrieval suggests conditional models outperform language modeling approaches, for some tasks. This book is addressed to students and professionals working on language technology systems that are dependent on sentence or passage retrieval. N° de réf. du vendeur 9783639453614
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Vendeur : Books Puddle, Woodside, NY, Etats-Unis
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Vendeur : Majestic Books, Hounslow, Royaume-Uni
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Exploring Sentence Retrieval | Vanessa Murdock | Taschenbuch | Paperback | 180 S. | Englisch | 2012 | AV Akademikerverlag | EAN 9783639453614 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 106323567
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Revision with unchanged content. Sentence Retrieval is the task of retrieving a relevant sentence in response to a query, a question, or a reference sentence. In this work we begin by demonstrating that because sentences are much smaller than documents, the performance of typical document retrieval systems on the retrieval of sentences is significantly worse. We propose several solutions to the problem of sentence retrieval, based on statistical translation models, and investigate these solutions the application areas of sentence retrieval for question answering, novelty detection, and information provenance. Statistical translation models are appropriate for tasks where the sentence to be retrieved benefits from the addition of related terms and synonyms. The context of a sentence affects its meaning, and smoothing from the local context of the sentence improves retrieval. A brief investigation of conditional models for sentence retrieval suggests conditional models outperform language modeling approaches, for some tasks. This book is addressed to students and professionals working on language technology systems that are dependent on sentence or passage retrieval.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 180 pp. Englisch. N° de réf. du vendeur 9783639453614
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Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
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