The Community for Technology Leaders
RSS Icon
Issue No.06 - June (2011 vol.23)
pp: 831-844
Danushka Bollegala , The University of Tokyo, Tokyo
Yutaka Matsuo , The University of Tokyo, Tokyo
Mitsuru Ishizuka , The University of Tokyo, Tokyo
An individual is typically referred by numerous name aliases on the web. Accurate identification of aliases of a given person name is useful in various web related tasks such as information retrieval, sentiment analysis, personal name disambiguation, and relation extraction. We propose a method to extract aliases of a given personal name from the web. Given a personal name, the proposed method first extracts a set of candidate aliases. Second, we rank the extracted candidates according to the likelihood of a candidate being a correct alias of the given name. We propose a novel, automatically extracted lexical pattern-based approach to efficiently extract a large set of candidate aliases from snippets retrieved from a web search engine. We define numerous ranking scores to evaluate candidate aliases using three approaches: lexical pattern frequency, word co-occurrences in an anchor text graph, and page counts on the web. To construct a robust alias detection system, we integrate the different ranking scores into a single ranking function using ranking support vector machines. We evaluate the proposed method on three data sets: an English personal names data set, an English place names data set, and a Japanese personal names data set. The proposed method outperforms numerous baselines and previously proposed name alias extraction methods, achieving a statistically significant mean reciprocal rank (MRR) of 0.67. Experiments carried out using location names and Japanese personal names suggest the possibility of extending the proposed method to extract aliases for different types of named entities, and for different languages. Moreover, the aliases extracted using the proposed method are successfully utilized in an information retrieval task and improve recall by 20 percent in a relation-detection task.
Web mining, information extraction, web text analysis.
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuka, "Automatic Discovery of Personal Name Aliases from the Web", IEEE Transactions on Knowledge & Data Engineering, vol.23, no. 6, pp. 831-844, June 2011, doi:10.1109/TKDE.2010.162
[1] R. Guha and A. Garg, "Disambiguating People in Search," technical report, Stanford Univ., 2004.
[2] J. Artiles, J. Gonzalo, and F. Verdejo, "A Testbed for People Searching Strategies in the WWW," Proc. SIGIR '05, pp. 569-570, 2005.
[3] G. Mann and D. Yarowsky, "Unsupervised Personal Name Disambiguation," Proc. Conf. Computational Natural Language Learning (CoNLL '03), pp. 33-40, 2003.
[4] R. Bekkerman and A. McCallum, "Disambiguating Web Appearances of People in a Social Network," Proc. Int'l World Wide Web Conf. (WWW '05), pp. 463-470, 2005.
[5] G. Salton and M. McGill, Introduction to Modern Information Retreival. McGraw-Hill Inc., 1986.
[6] M. Mitra, A. Singhal, and C. Buckley, "Improving Automatic Query Expansion," Proc. SIGIR '98, pp. 206-214, 1998.
[7] P. Cimano, S. Handschuh, and S. Staab, "Towards the Self-Annotating Web," Proc. Int'l World Wide Web Conf. (WWW '04), 2004.
[8] Y. Matsuo, J. Mori, M. Hamasaki, K. Ishida, T. Nishimura, H. Takeda, K. Hasida, and M. Ishizuka, "Polyphonet: An Advanced Social Network Extraction System," Proc. WWW '06, 2006.
[9] P. Turney, "Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews," Proc. Assoc. for Computational Linguistics (ACL '02), pp. 417-424, 2002.
[10] A. Bagga and B. Baldwin, "Entity-Based Cross-Document Coreferencing Using the Vector Space Model," Proc. Int'l Conf. Computational Linguistics (COLING '98), pp. 79-85, 1998.
[11] C. Galvez and F. Moya-Anegon, "Approximate Personal Name-Matching through Finite-State Graphs," J. Am. Soc. for Information Science and Technology, vol. 58, pp. 1-17, 2007.
[12] M. Bilenko and R. Mooney, "Adaptive Duplicate Detection Using Learnable String Similarity Measures," Proc. SIGKDD '03, 2003.
[13] T. Hokama and H. Kitagawa, "Extracting Mnemonic Names of People from the Web," Proc. Ninth Int'l Conf. Asian Digital Libraries (ICADL '06), pp. 121-130, 2006.
[14] M. Hearst, "Automatic Acquisition of Hyponyms from Large Text Corpora," Proc. Int'l Conf. Computational Linguistics (COLING '92), pp. 539-545, 1992.
[15] M. Berland and E. Charniak, "Finding Parts in Very Large Corpora," Proc. Ann. Meeting of the Assoc. for Computational Linguistics (ACL '99), pp. 57-64, 1999.
[16] S. Chakrabarti, Mining the Web: Discovering Knowledge from Hypertext Data. Morgan Kaufmann, 2003.
[17] G. Salton and C. Buckley, "Term-Weighting Approaches in Automatic Text Retrieval," Information Processing and Management, vol. 24, pp. 513-523, 1988.
[18] C. Manning and H. Schutze, Foundations of Statistical Natural Language Processing. MIT Press, 1999.
[19] T. Dunning, "Accurate Methods for the Statistics of Surprise and Coincidence," Computational Linguistics, vol. 19, pp. 61-74, 1993.
[20] K. Church and P. Hanks, "Word Association Norms, Mutual Information and Lexicography," Computational Linguistics, vol. 16, pp. 22-29, 1991.
[21] T. Hisamitsu and Y. Niwa, "Topic-Word Selection Based on Combinatorial Probability," Proc. Natural Language Processing Pacific-Rim Symp. (NLPRS '01), pp. 289-296, 2001.
[22] F. Smadja, "Retrieving Collocations from Text: Xtract," Computational Linguistics, vol. 19, no. 1, pp. 143-177, 1993.
[23] D. Bollegala, Y. Matsuo, and M. Ishizuka, "Measuring Semantic Similarity between Words Using Web Search Engines," Proc. Int'l World Wide Web Conf. (WWW '07), pp. 757-766, 2007.
[24] T. Joachims, "Optimizing Search Engines Using Clickthrough Data," Proc. ACM SIGKDD '02, 2002.
[25] T. Kudo, K. Yamamoto, and Y. Matsumoto, "Applying Conditional Random Fields to Japanese Morphological Analysis," Proc. Conf. Empirical Methods in Natural Language (EMNLP '04), 2004.
[26] R. Baeza-Yates and B. Ribeiro-Neto, Modern Information Retrieval. ACM Press/Addison-Wesley, 1999.
[27] P. Mika, "Ontologies Are Us: A Unified Model of Social Networks and Semantics," Proc. Int'l Semantic Web Conf. (ISWC '05), 2005.
[28] S. Sekine and J. Artiles, "Weps 2 Evaluation Campaign: Overview of the Web People Search Attribute Extraction Task," Proc. Second Web People Search Evaluation Workshop (WePS '09) at 18th Int'l World Wide Web Conf., 2009.
21 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool