The Information Retrieval Series

A Feature-Centric View of Information Retrieval

Authors: Metzler, Donald

  • Presents a novel paradigm for Web search, which is especially applicable to large data sets
  • Combines experiences from the author’s academic and industrial research over several years
  • Delivers the single most comprehensive source for feature-based information retrieval models
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  • ISBN 978-3-642-22898-8
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About this book

Commercial Web search engines such as Google, Yahoo, and Bing are used every day by millions of people across the globe. With their ever-growing refinement and usage, it has become increasingly difficult for academic researchers to keep up with the collection sizes and other critical research issues related to Web search, which has created a divide between the information retrieval research being done within academia and industry.  Such large collections pose a new set of challenges for information retrieval researchers.

In this work, Metzler describes highly effective information retrieval models for both smaller, classical data sets, and larger Web collections. In a shift away from heuristic, hand-tuned ranking functions and complex probabilistic models, he presents feature-based retrieval models. The Markov random field model he details goes beyond the traditional yet ill-suited bag of words assumption in two ways. First, the model can easily exploit various types of dependencies that exist between query terms, eliminating the term independence assumption that often accompanies bag of words models. Second, arbitrary textual or non-textual features can be used within the model. As he shows, combining term dependencies and arbitrary features results in a very robust, powerful retrieval model. In addition, he describes several extensions, such as an automatic feature selection algorithm and a query expansion framework. The resulting model and extensions provide a flexible framework for highly effective retrieval across a wide range of tasks and data sets.

A Feature-Centric View of Information Retrieval provides graduate students, as well as academic and industrial researchers in the fields of information retrieval and Web search with a modern perspective on information retrieval modeling and Web searches.

About the authors

Donald Metzler is a Research Scientist in the Natural Language Group at the University of Southern California's Information Sciences Institute. Prior to that he was a Research Scientist in the Search and Computational Advertising group at Yahoo! Research. He received his Ph.D. from the University of Massachusetts in 2007. He is an active member of the information retrieval and Web search communities, having served on the program committees of SIGIR, WWW, WSDM, HLT, EMNLP, and ICML. He has published over 35 research papers, and has 16 patents pending. His research interests include information retrieval, Web search, computational advertising, and applications of machine learning to large-scale text problems.

Reviews

From the reviews:

“This book is organized in 6 chapters (Introduction, Classical retrieval models, Feature-based ranking, Feature-based query expansion, Query-dependent feature weighting, Model learning), two appendices (Data sets and Evaluation metrics) and a comprehensive bibliography. … The book is recommended for an advanced master’s or PhD-level course in information retrieval, being also a valuable reference for the researchers with professional interests in this domain.” (Mirel Cosulschi, Zentralblatt MATH, Vol. 1235, 2012)

Table of contents (6 chapters)

Buy this book

eBook $84.99
price for USA
  • ISBN 978-3-642-22898-8
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Hardcover $109.00
price for USA
  • ISBN 978-3-642-22897-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $109.00
price for USA
  • ISBN 978-3-642-27017-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
A Feature-Centric View of Information Retrieval
Authors
Series Title
The Information Retrieval Series
Series Volume
27
Copyright
2011
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-642-22898-8
DOI
10.1007/978-3-642-22898-8
Hardcover ISBN
978-3-642-22897-1
Softcover ISBN
978-3-642-27017-8
Series ISSN
1387-5264
Edition Number
1
Number of Pages
XII, 168
Topics