Unsupervised relation extraction by mining Wikipedia texts using information from the web

ABSTRACT

This paper presents an unsupervised relation extraction method for discovering and enhancing relations in which a specified concept in Wikipedia participates. Using respective characteristics of Wikipedia articles and Web corpus, we develop a clustering approach based on combinations of patterns: dependency patterns from dependency analysis of texts in Wikipedia, and surface patterns generated from highly redundant information related to the Web. Evaluations of the proposed approach on two different domains demonstrate the superiority of the pattern combination over existing approaches. Fundamentally, our method demonstrates how deep linguistic patterns contribute complementarily with Web surface patterns to the generation of various relations.

References

1. Michele Banko, Michael J. Cafarella, Stephen Soderland, Matt Broadhead and Oren Etzioni. 2007. Open information extraction from the Web. In Proceedings of IJCAI-2007.
2. Danushka Bollegala, Yutaka Matsuo and Mitsuru Ishizuka. 2007. Measuring Semantic Similarity between Words Using Web Search Engines. In Proceedings of WWW-2007.
3. Razvan C. Bunescu and Raymond J. Mooney. 2005. A shortest path dependency kernel for relation extraction. In Proceedings of HLT/EMLNP-2005.
4. Jinxiu Chen, Donghong Ji, Chew Lim Tan and Zhengyu Niu. 2005. Unsupervised Feature Selection for Relation Extraction. In Proceedings of IJCNLP-2005.
5. Aron Culotta and Jeffrey Sorensen. 2004. Dependency tree kernels for relation extraction. In Proceedings of the ACL-2004.
6. Dmitry Davidov, Ari Rappoport and Moshe Koppel. 2007. Fully unsupervised discovery of concept-specific relationships by Web mining. In Proceedings of ACL-2007.
7. Dmitry Davidov and Ari Rappoport. 2008. Classification of Semantic Relationships between Nominals Using Pattern Clusters. In Proceedings of ACL-2008.
8. Wei Fan, Kun Zhang, Hong Cheng, Jing Gao, Xifeng Yan, Jiawei Han, Philip S. Yu and Olivier Verscheure. 2008. Direct Mining of Discriminative and Essential Frequent Patterns via Model-based Search Tree. In Proceedings of KDD-2008.
9. Evgeniy Gabrilovich and Shaul Markovitch. 2006. Overcoming the brittleness bottleneck using wikipedia: Enhancing text categorization with encyclopedic knowledge. In Proceedings of AAAI-2006.
10. Jim Giles. 2005. Internet encyclopaedias go head to head. Nature 438:900C901.
11. Sanda Harabagiu, Cosmin Adrian Bejan and Paul Morarescu. 2005. Shallow semantics for relation extraction. In Proceedings of IJCAI-2005.
12. Takaaki Hasegawa, Satoshi Sekine and Ralph Grishman. 2004. Discovering Relations among Named Entities from Large Corpora. In Proceedings of ACL-2004.
13. Nanda Kambhatla. 2004. Combining lexical, syntactic and semantic features with maximum entropy models. In Proceedings of ACL-2004.
14. Dat P. T. Nguyen, Yutaka Matsuo and Mitsuru Ishizuka. 2007. Relation extraction from Wikipedia using subtree mining. In Proceedings of AAAI-2007.
15. Patrick Pantel and Marco Pennacchiotti. 2006. Espresso: Leveraging generic patterns for automatically harvesting semantic relations. In Proceedings of ACL-2006.
16. Benjamin Rosenfeld and Ronen Feldman. 2006. URES: an Unsupervised Web Relation Extraction System. In Proceedings of COLING/ACL-2006.
17. Benjamin Rosenfeld and Ronen Feldman. 2007. Clustering for Unsupervised Relation Identification. In Proceedings of CIKM-2007.
18. Peter D. Turney. 2006. Expressing implicit semantic relations without supervision. In Proceedings of ACL-2006.
19. Max Volkel, Markus Krotzsch, Denny Vrandecic, Heiko Haller and Rudi Studer. 2006. Semantic wikipedia. In Proceedings of WWW-2006.
20. Mohammed J. Zaki. 2002. Efficiently mining frequent trees in a forest. In Proceedings of SIGKDD-2002.
21. Min Zhang, Jie Zhang, Jian Su and Guodong Zhou. 2006. A Composite Kernel to Extract Relations between Entities with both Flat and Structured Features. In Proceedings of ACL-2006.

Index Terms

• Applied computing

  • Document management and text processing

• Computing methodologies

  • Artificial intelligence

    • Natural language processing

  • Machine learning

• Information systems

  • Information retrieval

    • Evaluation of retrieval results

  • Information systems applications

    • Data mining