Abstract
In this paper, we propose an unsupervised approach for multi-polarization of topic person names. We employ a model-based EM method to polarize individuals into positively correlated groups. In addition, we present off-topic block elimination and weighted correlation coefficient techniques to eliminate the off-topic blocks and reduce the text sparseness problem respectively. Our experiment results demonstrate that the proposed method can identify multi-polar person groups of topics correctly.
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References
Chen, C.C., Wu, C.-Y.: Bipolar person name identification of topic documents using principal component analysis. In: Proceedings of the 23rd International Conference on Computational Linguistics, pp. 170–178. Association for Computational Linguistics, Beijing (2010)
Chen, C.C., Chen, Z.-Y., Wu, C.-Y.: An Unsupervised Approach for Person Name Bipolarization Using Principal Component Analysis. IEEE Transactions on Knowledge and Data Engineering (to appear, 2012)
Ding, X., Liu, B., Yu, P.S.: A holistic lexicon-based approach to opinion mining. In: Proceedings of the International Conference on Web Search and Web Data Mining, pp. 231–240. ACM, Palo Alto (2008)
Feng, A., Allan, J.: Finding and linking incidents in news. In: Proceedings of the Sixteenth ACM Conference on Information and Knowledge Management, pp. 821–830. ACM, Lisbon (2007)
Ganapathibhotla, M., Liu, B.: Mining opinions in comparative sentences. In: Proceedings of the 22nd International Conference on Computational Linguistics, vol. 1, pp. 241–248. Association for Computational Linguistics, Manchester (2008)
Hatzivassiloglou, V., McKeown, K.R.: Predicting the semantic orientation of adjectives. In: Proceedings of the Eighth Conference on European Chapter of the Association for Computational Linguistics, pp. 174–181. Association for Computational Linguistics, Madrid (1997)
Hofmann, T.: Probabilistic latent semantic indexing. In: Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 50–57. ACM, Berkeley (1999)
Hu, M., Liu, B.: Mining opinion features in customer reviews. In: Proceedings of the 19th National Conference on Artifical Intelligence, pp. 755–760. AAAI Press, San Jose (2004)
Kanayama, H., Nasukawa, T.: Fully automatic lexicon expansion for domain-oriented sentiment analysis. In: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing, pp. 355–363. Association for Computational Linguistics, Sydney (2006)
Kim, S.-M., Hovy, E.: Determining the sentiment of opinions. In: Proceedings of the 20th International Conference on Computational Linguistics, p. 1367. Association for Computational Linguistics, Geneva (2004)
Ku, L.W., Liang, Y.T., Chen, H.H.: Opinion extraction, summarization and tracking in news and blog corpora. In: Proceedings of AAAI 2006 Spring Symposium on Computational Approaches to Analyzing Weblogs (2006)
Manning, C.D., Raghavan, P., Schütze, H.: Introduction to information retrieval. Cambridge University Press (2008)
Mei, Q., Zhai, C.: Discovering evolutionary theme patterns from text: an exploration of temporal text mining. In: Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery in Data Mining, pp. 198–207. ACM, Chicago (2005)
Miller, G.A., Beckwith, R., Fellbaum, C., Gross, D., Miller, K.J.: Introduction to WordNet: An On-line Lexical Database*. International Journal of Lexicography 3, 235–244 (1990)
Mitchell, T.: Machine learning. MacGraw-Hill (1997)
Nallapati, R., Feng, A., Peng, F., Allan, J.: Event threading within news topics. In: Proceedings of the Thirteenth ACM International Conference on Information and Knowledge Management, pp. 446–453. ACM, Washington, D.C (2004)
Pang, B., Lee, L.: Opinion Mining and Sentiment Analysis. Found. Trends Inf. Retr. 2, 1–135 (2008)
Salton, G.: Automatic text processing: the transformation, analysis and retrieval of information by computer (1989)
Schütze, H.: Foundations of statistical natural language processing. The MIT Press (1999)
Stone, P., Dunphy, D., Smith, M., Ogilvie, D.: The General Inquirer: A Computer Approach to Content Analysis. MIT Press (1966)
Turney, P.D., Littman, M.L.: Measuring praise and criticism: Inference of semantic orientation from association. ACM Trans. Inf. Syst. 21, 315–346 (2003)
Wu, C.F.J.: On the Convergence Properties of the EM Algorithm. The Annals of Statistics 11, 95–103 (1983)
Zipf, G.K.: Human behavior and the principle of least effort: an introduction to human ecology. Addison-Wesley Press (1949)
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Chen, C.C., Chen, ZY. (2011). A Model-Based EM Method for Topic Person Name Multi-polarization. In: Salem, M.V.M., Shaalan, K., Oroumchian, F., Shakery, A., Khelalfa, H. (eds) Information Retrieval Technology. AIRS 2011. Lecture Notes in Computer Science, vol 7097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25631-8_37
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DOI: https://doi.org/10.1007/978-3-642-25631-8_37
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