Statistical Language Models for Information Retrieval

Chengxiang Zhai

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Idioma: inglés

Editorial: Springer, Springer Dez 2008, 2008

3031010027 / 9783031010026

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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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This item is printed on demand - Print on Demand Titel. Neuware -As online information grows dramatically, search engines such as Google are playing a more and more important role in our lives. Critical to all search engines is the problem of designing an effective retrieval model that can rank documents accurately for a given query. This has been a central research problem in information retrieval for several decades. In the past ten years, a new generation of retrieval models, often referred to as statistical language models, has been successfully applied to solve many different information retrieval problems. Compared with the traditional models such as the vector space model, these new models have a more sound statistical foundation and can leverage statistical estimation to optimize retrieval parameters. They can also be more easily adapted to model non-traditional and complex retrieval problems. Empirically, they tend to achieve comparable or better performance than a traditional model with less effort on parameter tuning. This book systematically reviews the large body of literature on applying statistical language models to information retrieval with an emphasis on the underlying principles, empirically effective language models, and language models developed for non-traditional retrieval tasks. All the relevant literature has been synthesized to make it easy for a reader to digest the research progress achieved so far and see the frontier of research in this area. The book also offers practitioners an informative introduction to a set of practically useful language models that can effectively solve a variety of retrieval problems. No prior knowledge about information retrieval is required, but some basic knowledge about probability and statistics would be useful for fully digesting all the details. Table of Contents: Introduction / Overview of Information Retrieval Models / Simple Query Likelihood Retrieval Model / Complex Query Likelihood Model / Probabilistic Distance Retrieval Model / Language Models for Special Retrieval Tasks / Language Models for Latent Topic Analysis / ConclusionsSpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 144 pp. Englisch.…

N° de ref. del artículo 9783031010026

Título
Statistical Language Models for Information Retrieval
Autor
Chengxiang Zhai
Editorial
Springer, Springer Dez 2008
Año de publicación
2008
Estado
Neu
Encuadernación
Taschenbuch
Idioma
inglés
ISBN 10
3031010027
ISBN 13
9783031010026
Peso del artículo
284 gramos
Dimensiones
235x191x9 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Alemania

Vendedor de 5 estrellas

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