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Statistical Language Models for Information Retrieval (Paperback)
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Statistical Language Models for Information Retrieval (Paperback)
Series: Synthesis Lectures on Human Language Technologies
Expected to ship within 10 - 15 working days
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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 / Conclusions
General
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