Reexamining the Cluster Hypothesis: Scatter/Gather on Retrieval Results.

Marti A. Hearst, Jan O. Pedersen: Reexamining the Cluster Hypothesis: Scatter/Gather on Retrieval Results. SIGIR 1996: 76-84

@inproceedings{DBLP:conf/sigir/HearstP96,
  author    = {Marti A. Hearst and
               Jan O. Pedersen},
  editor    = {Hans-Peter Frei and
               Donna Harman and
               Peter Sch{\"a}uble and
               Ross Wilkinson},
  title     = {Reexamining the Cluster Hypothesis: Scatter/Gather on Retrieval
               Results},
  booktitle = {Proceedings of the 19th Annual International ACM SIGIR Conference
               on Research and Development in Information Retrieval, SIGIR'96,
               August 18-22, 1996, Zurich, Switzerland (Special Issue of the
               SIGIR Forum)},
  publisher = {ACM},
  year      = {1996},
  isbn      = {0-89791-792-8},
  pages     = {76-84},
  ee        = {db/conf/sigir/HearstP96.html},
  crossref  = {DBLP:conf/sigir/96},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

BibTeX

Abstract

We present Scatter/Gather, a cluster-based document browsing method, as an alternative to ranked titles for the organization and viewing of retrieval results. We systematically evaluate Scatter/Gather in this context and find significant improvements over similarity search ranking alone. This result provides evidence validating the cluster hypothesis which states that relevant documents tend to be more similar to each other than to non-relevant documents. We describe a system employing Scatter/Gather and demonstrate that users are able to use this system close to its full potential.

Copyright © 1996 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.

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BibTeX

Printed Edition

Hans-Peter Frei, Donna Harman, Peter Schäuble, Ross Wilkinson (Eds.): Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'96, August 18-22, 1996, Zurich, Switzerland (Special Issue of the SIGIR Forum). ACM 1996, ISBN 0-89791-792-8
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Online Edition: ACM Digital Library

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Referenced by

Philip S. Yu: Data Mining and Personalization Technologies. DASFAA 1999: 6-13
Koji Eguchi, Hidetaka Ito, Akira Kumamoto, Yakichi Kanata: Adaptive and Incremental Query Expansion for Cluster-based Browsing. DASFAA 1999: 25-34
Kai Korpimies, Esko Ukkonen: Term Weighting in Query-Based Document Clustering (Extended Abstract). ADBIS 1998: 151-153

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