Weakly-supervised discovery of named entities using web search queries

ABSTRACT

A seed-based framework for textual information extraction allows for weakly supervised extraction of named entities from anonymized Web search queries. The extraction is guided by a small set of seed named entities, without any need for handcrafted extraction patterns or domain-specific knowledge, allowing for the acquisition of named entities pertaining to various classes of interest to Web search users. Inherently noisy search queries are shown to be a highly valuable, albeit little explored, resource for Web-based named entity discovery.

References

1. E. Brill and P. Resnik. A transformation-based approach to prepositional phrase attachment disambiguation. In Proceedings of the 15th International Conference on Computational Linguistics (COLING-94), pages 1198--1204, Kyoto, Japan, 1994.
2. M. Cafarella, D. Downey, S. Soderland, and O. Etzioni. KnowItNow: Fast, scalable information extraction from the Web. In Proceedings of the Human Language Technology Conference (HLT-EMNLP-05), pages 563--570, Vancouver, Canada, 2005.
3. M. Collins and Y. Singer. Unsupervised models for named entity classification. In Proceedings of the 1999 Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/VLC-99), pages 189--196, College Park, Maryland, 1999.
4. S. Cucerzan and D. Yarowsky. Language independent named entity recognition combining morphological and contextual evidence. In Proceedings of the 1999 Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/VLC-99), pages 90--99, College Park, Maryland, 1999.
5. H. Cui, J. Wen, J. Nie, and W. Ma. Probabilistic query expansion using query logs. In Proceedings of the 11th World Wide Web Conference (WWW-02), pages 325--332, Honolulu, Hawaii, 2002.
6. A. Klementiev and D. Roth. Weakly supervised named entity transliteration and discovery from multilingual comparable corpora. In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics (COLING-ACL-06), pages 817--824, Sydney, Australia, 2006.
7. L. Lee. Measures of distributional similarity. In Proceedings of the 37th Annual Meeting of the Association of Computational Linguistics (ACL-99), pages 25--32, College Park, Maryland, 1999.
8. M. Li, M. Zhu, Y. Zhang, and M. Zhou. Exploring distributional similarity based models for query spelling correction. In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics (COLING-ACL-06), pages 1025--1032, Sydney, Australia, 2006.
9. K. McCarthy and W. Lehnert. Using decision trees for coreference resolution. In Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI-95), pages 1050--1055, Montreal, Quebec, 1995.
10. R. Mooney and R. Bunescu. Mining knowledge from text using information extraction. SIGKDD Explorations, 7(1):3--10, 2005.
11. M. Paşca. Acquisition of categorized named entities for Web search. In Proceedings of the 13th ACM Conference on Information and Knowledge Management (CIKM-04), Washington, D.C., 2004.
12. M. Paşca. Organizing and searching the World Wide Web of facts - step two: Harnessing the wisdom of the crowds. In Proceedings of the 16th World Wide Web Conference (WWW-07), pages 101--110, Banff, Canada, 2007.
13. P. Pantel and D. Ravichandran. Automatically labeling semantic classes. In Proceedings of the 2004 Human Language Technology Conference (HLT-NAACL-04), pages 321--328, Boston, Massachusetts, 2004.
14. E. Riloff. Automatically generating extraction patterns from untagged text. In Proceedings of the 13th National Conference on Artificial Intelligence (AAAI-96), pages 1044--1049, Portland, Oregon, 1996.
15. E. Riloff and R. Jones. Learning dictionaries for information extraction by multi-level bootstrapping. In Proceedings of the 16th National Conference on Artificial Intelligence (AAAI-99), pages 474--479, Orlando, Florida, 1999.
16. L. Schubert. Turing's dream and the knowledge challenge. In Proceedings of the 21st National Conference on Artificial Intelligence (AAAI-06), Boston, Massachusetts, 2006.
17. Y. Shinyama and S. Sekine. Named entity discovery using comparable news articles. In Proceedings of the 20th International Conference on Computational Linguistics (COLING-04), pages 848--853, Geneva, Switzerland, 2004.
18. M. Stevenson and R. Gaizauskas. Using corpus-derived name lists for named entity recognition. In Proceedings of the 6th Conference on Applied Natural Language Processing (ANLP-00), Seattle, Washington, 2000.
19. P. Talukdar, T. Brants, M. Liberman, and F. Pereira. A context pattern induction method for named entity extraction. In Proceedings of the 10th Conference on Computational Natural Language Learning (CoNLL-X), pages 141--148, New York, New York, 2006.
20. M. Thelen and E. Riloff. A bootstrapping method for learning semantic lexicons using extraction pattern contexts. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP-02), pages 214--221, Philadelphia, Pennsylvania, 2002.
21. Z. Zhuang and S. Cucerzan. Re-ranking search results using query logs. In Proceedings of the 15th International Conference on Information and Knowledge Management (CIKM-06), pages 860--861, Arlington, Virginia, 2006.

Index Terms

• Computing methodologies

  • Artificial intelligence

    • Natural language processing

  • Machine learning

• Information systems

  • Information retrieval

    • Document representation