Network Theory and Applications

Clustering and Information Retrieval

Editors: Weili Wu, Hui Xiong, Shekhar, Shashi (Eds.)

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About this book

Clustering is an important technique for discovering relatively dense sub-regions or sub-spaces of a multi-dimension data distribution. Clus­ tering has been used in information retrieval for many different purposes, such as query expansion, document grouping, document indexing, and visualization of search results. In this book, we address issues of cluster­ ing algorithms, evaluation methodologies, applications, and architectures for information retrieval. The first two chapters discuss clustering algorithms. The chapter from Baeza-Yates et al. describes a clustering method for a general metric space which is a common model of data relevant to information retrieval. The chapter by Guha, Rastogi, and Shim presents a survey as well as detailed discussion of two clustering algorithms: CURE and ROCK for numeric data and categorical data respectively. Evaluation methodologies are addressed in the next two chapters. Ertoz et al. demonstrate the use of text retrieval benchmarks, such as TRECS, to evaluate clustering algorithms. He et al. provide objective measures of clustering quality in their chapter. Applications of clustering methods to information retrieval is ad­ dressed in the next four chapters. Chu et al. and Noel et al. explore feature selection using word stems, phrases, and link associations for document clustering and indexing. Wen et al. and Sung et al. discuss applications of clustering to user queries and data cleansing. Finally, we consider the problem of designing architectures for infor­ mation retrieval. Crichton, Hughes, and Kelly elaborate on the devel­ opment of a scientific data system architecture for information retrieval.

Table of contents (10 chapters)

  • Clustering in Metric Spaces with Applications to Information Retrieval

    Baeza-Yates, Ricardo (et al.)

    Pages 1-33

  • Techniques for Clustering Massive Data Sets

    Guha, Sudipto (et al.)

    Pages 35-82

  • Finding Topics in Collections of Documents: A Shared Nearest Neighbor Approach

    Ertöz, Levent (et al.)

    Pages 83-103

  • On Quantitative Evaluation of Clustering Systems

    He, Ji (et al.)

    Pages 105-133

  • Techniques for Textual Document Indexing and Retrieval via Knowledge Sources and Data Mining

    Chu, Wesley W. (et al.)

    Pages 135-159

Buy this book

eBook $179.00
price for USA (gross)
  • ISBN 978-1-4613-0227-8
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $229.00
price for USA
  • ISBN 978-1-4020-7682-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $229.00
price for USA
  • ISBN 978-1-4613-7949-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Clustering and Information Retrieval
Editors
  • Weili Wu
  • Hui Xiong
  • Shashi Shekhar
Series Title
Network Theory and Applications
Series Volume
11
Copyright
2004
Publisher
Springer US
Copyright Holder
Kluwer Academic Publishers
eBook ISBN
978-1-4613-0227-8
DOI
10.1007/978-1-4613-0227-8
Hardcover ISBN
978-1-4020-7682-4
Softcover ISBN
978-1-4613-7949-2
Series ISSN
1568-1696
Edition Number
1
Number of Pages
VIII, 330
Topics