Automatically labeling hierarchical clusters

ACM International Conference Proceeding Series

Volumn 151, Issue , 2006, Pages 167-176

  Treeratpituk, Pucktada ^a   Callan, Jamie ^a  

^a Carnegie Mellon University   (United States)

Author keywords

Cluster labeling; Document hierarchy

Indexed keywords

HIERARCHICAL SYSTEMS; INFORMATION ANALYSIS; LOGIC PROGRAMMING;

CLUSTER LABELING; INTERACTIVE BROWSING; OPEN DIRECTORY PROJECT (ODP);

CLUSTERING ALGORITHMS;

EID: 34250771586     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1146598.1146650     Document Type: Conference Paper

References (16)

1. Caraballo, S. Automatic Acquisition of a hypernym-labeled noun hierarchy from text. In Proceedings of the Association for Computational Linguistics Conference, 1999.
2. th International Conference on Information and Knowledge Management, 2004.
3. Cutting D. R., Karger D. R., and Pederson J. O. Constant interaction-time Scatter/Gather browsing of very large document collections. In Proceedings of International ACM Conference on Research and Development in Information Retrieval, 1993.
4. th International Conference on Information and Knowledge Management, 2002.
5. Glover, E., Tsioutsiouliklis, K., Lawrence, S., Pennock, D., and Flake, G. Using web structure for classifying and describing web pages. In Proceedings of International Conference on World Wide Web, 2002.
6. Krovetz, R. Viewing morphology as an inference process. In Proceedings of International ACM Conference on Research and Development in Information Retrieval, 1993.
7. Lawrie, D., Croft, W. B., and Rosenberg, A. L. Finding topic words for hierarchical summarization. In Proceedings of international ACM conference on research and development in information retrieval, 2001.
8. nd Hawaii International Conference on System Science, 1999.
9. Pantel, P., and Ravichandran, D. Automatically labeling semantic classes. In Proceedings of the Human Language Technology and North American Chapter of the Association for Computational Linguistics Conference. 2004.
10. Popescul, A., and Ungar, L. Automatic labeling of document clusters. Unpublished manuscript, available at http://citeseer.nj.nec.com/ popescu00automatic.html, 2000.
11. Yang, H. and Callan, J. Near-duplicate detection for eRulemaking. In Proceedings of the National Conference on Digital Government Research (DG.02005), 2005.
12. Zeng, H., He, Q., Chen Z., Ma, W., and Ma J. Learning to cluster web search results. In Proceedings of International ACM Conference on Research and Development in Information Retrieval, 2004.
13. Open Directory Project (ODP).
14. eRulemaking Testbed. http://hartford.lti.cs.cmu.edu/eRulemaking/Data. html.
15. Weka, Data Mining Software, University of Waikato.
16. WordNet, a lexical database for the English language. [17] Yahoo!