Abstract
This work deals with determination of meaningful and terse cluster labels for News document clusters. We analyze a number of alternatives for selecting headlines and/or sentences of document in a document cluster (obtained as a result of an entity-event-duration query), and formalize an approach to extracting a short phrase from well-supported headlines/sentences of the cluster that can serve as the cluster label. Our technique maps a sentence into a set of significant stems to approximate its semantics, for comparison. Eventually a cluster label is extracted from a selected headline/sentence as a contiguous sequence of words, resuscitating word sequencing information lost in the formalization of semantic equivalence.
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References
Alonso, O., Gertz, M.: Clustering of Search Results using Temporal Attributes. In: Proceedings of 29th ACM SIGIR Conference, pp. 597–598 (2006)
Beil, F., Ester, F.M., Xu, X.: Frequent term-based text clustering. In: Proceedings of the 8th International Conference on Knowledge Discovery and Data Mining (KDD-2002), pp. 436–442 (2002)
Campos, R., Dias, G.: Automatic Hierarchical Clustering of Web Pages. In: Proceedings of the ELECTRA Workshop with 28th ACM SIGIR Conference, pp. 83–85 (2005)
Del Corso, G.M., Gulli, A., Romani, F.: Ranking a stream of news. In: Proceedings of 14th International World Wide Web Conference, Chiba, Japan, pp. 97–106 (2005)
Dunlavy, D., Conroy, J., O’Leary, D.: QCS: A Tool for Querying, Clsutering, and Summarizing Documents. In: Proceedings of HLT-NAACL, pp. 11–12 (2003)
Fung, B.C.M., Wang, K., Ester, M.: Hierarchical document clustering. In: Wang, J., (ed.) Encyclopedia of Data Warehousing and Mining, Idea Group (2005)
Ferragina, P., Gulli, A.: The anatomy of a hierarchical clustering engine for web-page, news and book snippets. In: Proceedings of the 4th IEEE International Conference on Data Mining, pp. 395–398 (2004)
Ferragina, P., Gulli, A.: A personalized search engine based on web-snippet hierarchical clustering. In: Proceedings of 14th International World Wide Web Conference, pp. 801–810 (2005)
Gulli, A.: The anatomy of a news search engine. In: Proceedings of 14th International World Wide Web Conference, pp. 880–881 (2005)
Gao, B.J., Ester, M.: Cluster description formats, problems and algorithms. In: Proceedings of the 6th SIAM Conference on Data Mining (2006)
Osinski, S., Weiss, D.: A concept-driven algorithm for clustering search results. IEEE Intelligent Systems 20, 48–54 (2005)
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Thirunarayan, K., Immaneni, T., Shaik, M.V. (2007). Selecting Labels for News Document Clusters. In: Kedad, Z., Lammari, N., Métais, E., Meziane, F., Rezgui, Y. (eds) Natural Language Processing and Information Systems. NLDB 2007. Lecture Notes in Computer Science, vol 4592. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73351-5_11
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DOI: https://doi.org/10.1007/978-3-540-73351-5_11
Publisher Name: Springer, Berlin, Heidelberg
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