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[1] Deerwester, S. , Dumais, S. T. , Furnas, G. W. , Landauer, T. K. , & Harshman, R. (1990) , "Indexing By Latent Semantic Analysis", Journal of the American Society For Information Science,41, 391-407. 10 [2] Griths T. L, and Steyvers M. (2004) , "Finding scientic topics", Proceedings of the National Academy of Sciences,101 (suppl. 1), 5228-5235. [3] Blei D. M., Ng A. Y., and Jordan M. I. (2003) , "Latent Dirichlet Allocation",Journal of Machine Learning Research, 3 : 993-1022. [4] Y. Yang, (1999) , "An evaluation of statistical approaches to text categorization", Information Retrieval, 1, pp. 69-90. [5] Lagus, K, Honkela, T., Kaski, S., and Kohonen, T. (1999) , "WEBSOM for textual data mining", Articial Intelligence Review, 13 (5{6), pp. 345-364. [6] Kaski, S. (1998) , " Dimensionality Reduction by Random Mapping: Fast Similarity Computation for Clustering", In Proceedings of IJCNN ’98, International Joint Conference on Neural Networks 1 413–418. IEEE Service Center: Piscataway, NJ. [7] Berry, M.W., Dumais, S. T., and O'Brien, G. W. (1995) , "Using linear algebra for intelligent information retrieval", SIAM Review, vol. 37, no. 4, pp. 573-595. [8] Hofmann, T. (1999) , "Probabilistic latent semantic indexing", in Proceedings of the 22nd International Conference on Research and Development in Information Retrieval (SIGIR'99) [9] Rosen-Zvi, M., Griths, T., Steyvers, M., Smyth, P. (2004), "The author-topic model for authors and documents", Proceedings of the 20th UAI Conference [10] Tang J., Zhang J., Yao L., Li J., Zhang L., and Su. Z. (2008), "Arnetminer: Extraction and mining of academic social networks". In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD’08), pages 990–998. [11] 楊瀟,馬軍,楊同峰,杜言琦,邵海敏(2010),"主題模型LDA的文檔自動文摘",智能系統學報 [12] 李文波,孫樂,黃瑞紅,馮元勇,張大鯤(2008),"基於Labeled-LDA模型的本文分類新算法”,第三屆全國信息檢索與內容安全學會會議 [13] Porter M(1980), Porter stemming algorithm, software available at http://nltk.googlecode.com/svn/trunk/doc/api/nltk.stem.porter-module.html [14] Chris Manning, Dan Jurafsky(2010), Stanford parser, software available at http://nlp.stanford.edu/software/lex-parser.shtml [15] Schutze, H., Hull, D. A, et.al. "A comparison of classifiers and document representations for the routing problem", In Proceedings of SIGIR-95, 1995. 229–237. [16] L Chen, N Tokuda, A Nagai (2003). "A new differential LSI space-based probabilistic document classifier", Information Processing Letters 2003,88(5):203-212 [17] Steyvers M., Smyth P., and Griffiths T. (2004). "Probabilistic author-topic models for information discovery. ", In Proc. of SIGKDD’04. [18] Griffiths T.L., Steyvers M., Blei D., and Tenenbaum J.B. "Integrating topics and syntax. " In Advances in Neural Information Processing Systems 17. MIT Press, Cambridge, MA, 2005. [19] McCallum A., Corrada Emmanuel A., and X. Wang. "The author-recipient-topic model for topic and role discovery in social networks". Technical Report UM-CS-2004-096, Department of Computer Science,University of Massachusetts, 2004. [20] Buntine W., Lofstrm J., Perki J., Perttu S., Poroshin V., Silander T., Tirri H., Tuominen A., and Tuulos. V."A scalable topic-based open source search engine". In IEEE/WIC/ACM International Conference on Web Intelligence, pages 228–234, 2004. [21] Blei D. and Lafferty J.. "Correlated topic models". In Neural Information Processing Systems, volume 18,2006. [22] Shou-de Lin and Hans Chalupsky ,”using unsupervised link discovery methods to find interesting facts and connections in a bibliography dataset”, in a bibliography dataset. SIGKDD Explorations, 5(2) 173-178, December 2003 [23] Shou-de Lin and Hans Chalupsky. Unsupervised Link Discovery in Multi-relational Data via Rarity Analysis. In Proceedings of the Third IEEE International Conference on Data Mining. Melbourne, Florida. 2003
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