Abstract
This paper focuses on subject shift in chronologically ordered news story streams, and presents a method for topic tracking which makes use of the subject-shift. For finding the discussion of a topic (we call it subject term), we applied keygraph method to each story. Similar to tf*idf method, keygraph is a term weighting method which is based on co-occurrence graphs consisting high frequency terms and their co-occurrence terms. Subject-shifts are identified based on the difference between two types of subject terms: one is extracted from a test story itself, and another is extracted from the test story by using topic terms (terms related to a topic) of initial positive training stories. The method was tested on the TDT English corpus, and the results showed that the system is competitive to other sites, even for a small number of initial positive training stories.
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References
Allan, J.: Incremental Relevance Feedback for Information Filtering. In: 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 270–278 (1996)
Allan, J., Carbonell, J., Doddington, G., Yamron, J., Yang, Y.: Topic Detection and Tracking Pilot Study Final Report. In: DARPA Broadcast News Transcription and Understanding Workshop (1998)
Allan, J., Papka, R., Lavrenko, V.: On-line New Event Detection and Tracking. In: DARPA Broadcast News Transcription and Understanding Workshop (1998)
Belkin, N.J., Croft, W.B.: Information Filtering and Information Retrieval: Two sides of the same coin? Communications of the ACM 35(2), 29–38 (1992)
Carbonell, J., Yang, Y., Lafferty, J., Brown, R.D., Pierce, T., Liu, X.: CMU Report on TDT-2: Segmentation, Detection and Tracking. In: DARPA Broadcast News Transcription and Understanding Workshop (1999)
Connell, M., Feng, A., Kumaran, G., Raghavan, H., Shah, C., Allan, J.: UMass at TDT 2004. In: DARPA Broadcast News Transcription and Understanding Workshop (2004)
Elsayed, T., Oard, D.W., Doermann, D.: TDT-2004: Adaptive Topic Tracking at Maryland. In: DARPA Broadcast News Transcription and Understanding Workshop (2004)
Fiscus, J.: Overview of the TDT 2001 Evaluation and Results. In: Workshop on TDT 2001 (2001)
Fiscus, J.G., Doddington, G.R.: Topic Detection and Tracking Evaluation Overview. In: Allan, J. (ed.) Topic Detection and Tracking. Kluwer Academic Publisher, Dordrecht (2002)
Franz, M., McCarley, J.S.: Unsupervised and Supervised Clustering for Topic Tracking. In: 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 310–317 (2001)
Harman, D.: Overview of the fourth Text REtrieval Conference (TREC4). In: 4th Text REtrieval Conference, TREC-4 (1996)
Joachims, T.: Estimating the Generalization Performance of an SVM Efficiently. In: 17th International Conference on Machine Learning, pp. 431–438 (2000)
Klinkenberg, R., Joachims, T.: Detecting Concept Drift with Support Vector Machines. In: 17th International Conference on Machine Learning, pp. 487–494 (2000)
Larkey, L.S., Feng, F., Connell, M., Lavernko, V.: Language-specific Model in Multilingual Topic Tracking. In: 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 402–409 (2004)
Lowe, S.A.: The Beta-binomial Mixture Model and its Application to TDT Tracking and Detection. In: DARPA Broadcast News Transcription and Understanding Workshop (1999)
Luhn, H.P.: The Automatic Creation of Literature Abstracts. IBM journal 2(1), 159–165 (1958)
Oard, D.W.: Topic Tracking with the PRISE Information Retrieval System. In: DARPA Broadcast News Transcription and Understanding Workshop, pp. 94–101 (1999)
Ohsawa, Y., Benson, N.E., Yachida, M.: KeyGraph: Automatic Indexing by Co-occurrence Graph Based on Building Construction Metaphor. In: Advances in Digital Libraries Conference, pp. 12–18 (1998)
Schmid, H.: Improvements in Part-of-Speech Tagging with an Application to German. In: EACL SIGDAT Workshop (1995)
Yang, Y., Ault, T., Pierce, T., Lattimer, C.W.: Improving Text Categorization Methods for Event Tracking. In: 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 65–72 (2000)
Zhang, Y., Callan, J.: CMU DIR Supervised Tracking Report. In: DARPA Broadcast News Transcription and Understanding Workshop (2004)
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Fukumoto, F., Suzuki, Y. (2009). Using Graph-Based Indexing to Identify Subject-Shift in Topic Tracking. In: Vetulani, Z., Uszkoreit, H. (eds) Human Language Technology. Challenges of the Information Society. LTC 2007. Lecture Notes in Computer Science(), vol 5603. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04235-5_34
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DOI: https://doi.org/10.1007/978-3-642-04235-5_34
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