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Scatter/Gather: A Cluster-based Approach to Browsing Large Document Collections
Abstract
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. 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.
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Cited by
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White, R. W., & Roth, R. A. (2009) · Synthesis lectures on information concepts, retrieval, and services · doi:10.2200/s00174ed1v01y200901icr003 · Cited by 632
Information foraging in information access environments
Pirolli, P., & Card, S. (1995) · Proceedings of the SIGCHI conference on Human factors in computing systems - CHI '95 · doi:10.1145/223904.223911 · Cited by 464
A Data-Clustering Algorithm on Distributed Memory Multiprocessors
Dhillon, I. S., & Modha, D. S. (2002) · Lecture Notes in Computer Science · doi:10.1007/3-540-46502-2_13 · Cited by 386
RankClus: integrating clustering with ranking for heterogeneous information network analysis
Sun, Y., Han, J., Zhao, P., Yin, Z., Cheng, H., & Wu, T. (2009) · Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology · doi:10.1145/1516360.1516426 · Cited by 382
Metadata
- Authors
- Cutting, D. R., Karger, D. R., Pedersen, J. O., & Tukey, J. W.
- Venue
- ACM SIGIR Forum
- Published
- 2017-08-02
- Volume
- 51
- Issue
- 2
- Pages
- 148-159
- ISSN
- 0163-5840 (ISSN-L)
- OpenAlex
- W1996764654
- Cited by
- 1,419
- References
- 0
- FWCI
- 53.49
- Type
- journal article
- Language
- en
- Open access
- closed
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- Cutting, D. R., Karger, D. R., Pedersen, J. O., & Tukey, J. W. (2017). Scatter/Gather: A Cluster-based Approach to Browsing Large Document Collections. ACM SIGIR Forum. https://doi.org/10.1145/3130348.3130362
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.