2007 UsingAKBtoDisambigPersonalName

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Subject Headings: Person Mention Resolution


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Results of queries by personal names often contain documents related to several people because of the namesake problem. In order to differentiate documents related to different people, an effective method is needed to measure document similarities and to find documents related to the same person. Some previous researchers have used the vector space model or have tried to extract common named entities for measuring similarities. We propose a new method that uses Web directories as a knowledge base to find shared contexts in document pairs and uses the measurement of shared contexts to determine similarities between document pairs. Experimental results show that our proposed method outperforms the vector space model method and the named entity recognition method.


1 T. Pedersen, A. Kulkarni, R. Angheluta, Z. Kozareva, T. Solorio. Name Discrimination by Clustering Similar Contexts. CICLing2005.

2 Ron Bekkerman, Andrew McCallum, Disambiguating Web appearances of people in a social network, Proceedings of the 14th International Conference on World Wide Web, May 10-14, 2005, Chiba, Japan doi:10.1145/1060745.1060813

3 Ramanathan V. Guha, A. Garg. Disambiguating People in Search. WWW2004.

4 http://www.alias-i.com/lingpipe

5 http://www.dmoz.org

6 http://www.google.com

7 Ricardo A. Baeza-Yates, Berthier Ribeiro-Neto, Modern Information Retrieval, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1999

8 Christopher D. Manning, Hinrich Schütze, Foundations of statistical natural language processing, MIT Press, Cambridge, MA, 1999

9 Amit Bagga, Breck Baldwin, Entity-based cross-document coreferencing using the Vector Space Model, Proceedings of the 17th International Conference on Computational linguistics, August 10-14, 1998, Montreal, Quebec, Canada

10 B. Malin. Unsupervised Name Disambiguation via Social Network Similarity. SIAM ICDM 2005.

11 Gideon S. Mann, David Yarowsky, Unsupervised personal name disambiguation, Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003, p.33-40, May 31, 2003, Edmonton, Canada doi:10.3115/1119176.1119181

12 Xiaojun Wan, Jianfeng Gao, Mu Li, Binggong Ding, Person resolution in person search results: WebHawk, Proceedings of the 14th ACM International Conference on Information and knowledge management, October 31-November 05, 2005, Bremen, Germany doi:10.1145/1099554.1099585

13 http://trec.nist.gov

14 http://dblp.uni-trier.de

15 http://www.amazon.com

16 http://www.tartarus.org/martin/PorterStemmer

17 Hinrich Schütze, Automatic word sense discrimination, Computational Linguistics, v.24 n.1, March 1998 18 Hui Han, Lee Giles, Hongyuan Zha, Cheng Li, Kostas Tsioutsiouliklis, Two supervised learning approaches for name disambiguation in author citations, Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries, June 07-11, 2004, Tuscon, AZ, USA doi:10.1145/996350.996419,

 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2007 UsingAKBtoDisambigPersonalNameQuang Minh Vu
Tomonari Masada
Atsuhiro Takasu
Jun Adachi
Using a knowledge base to disambiguate personal name in web search resultsProceedings of the 2007 ACM symposium on Applied Computinghttp://www.adl.nii.ac.jp/paper/vuminh sac2007.pdf10.1145/1244002.12441882007