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Scatter/Gather: A Cluster-based Approach to Browsing Large Document Collections

Author(s)
Cutting, Douglass R; Karger, David R; Pedersen, Jan O; Tukey, John W
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Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/
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Abstract
<jats:p>Document clustering has not been well received as an information retrieval tool. Objections to its use fall into two main categories: first, that clustering is too slow for large corpora (with running time often quadratic in the number of documents); and second, that clustering does not appreciably improve retrieval.</jats:p> <jats:p>We argue that these problems arise only when clustering is used in an attempt to improve conventional search techniques. However, looking at clustering as an information access tool in its own right obviates these objections, and provides a powerful new access paradigm. We present a document browsing technique that employs docum-ent clustering as its primary operation. We also present fast (linear time) clustering algorithm.</jats:p>
Date issued
2017
URI
https://hdl.handle.net/1721.1/134850
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science; Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Journal
ACM SIGIR Forum
Publisher
Association for Computing Machinery (ACM)

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