Discovering semantic biomedical relations utilizing the Web

ABSTRACT

To realize the vision of a Semantic Web for Life Sciences, discovering relations between resources is essential. It is very difficult to automatically extract relations from Web pages expressed in natural language formats. On the other hand, because of the explosive growth of information, it is difficult to manually extract the relations. In this paper we present techniques to automatically discover relations between biomedical resources from the Web. For this purpose we retrieve relevant information from Web Search engines and Pubmed database using various lexico-syntactic patterns as queries over SOAP web services. The patterns are initially handcrafted but can be progressively learnt. The extracted relations can be used to construct and augment ontologies and knowledge bases. Experiments are presented for general biomedical relation discovery and domain specific search to show the usefulness of our technique.

REFERENCES

• 1: Eugene Agichtein , Luis Gravano, Snowball: extracting relations from large plain-text collections, Proceedings of the fifth ACM conference on Digital libraries, p.85-94, June 02-07, 2000, San Antonio, Texas, United States [doi>10.1145/336597.336644]
• 2: Agichtein, E. and Gravano, L. 2003. Querying text databases for efficient information extraction. In Proceedings of the International Conference on Data Engineering (ICDE), U. Dayal, K. Ramamritham, and T. M. Vijayaraman, Eds. IEEE Computer Society, 113--124.
• 3: Matthew Berland , Eugene Charniak, Finding parts in very large corpora, Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics, p.57-64, June 20-26, 1999, College Park, Maryland [doi>10.3115/1034678.1034697]
• 4: Sergey Brin, Extracting Patterns and Relations from the World Wide Web, Selected papers from the International Workshop on The World Wide Web and Databases, p.172-183, March 27-28, 1998
• 5: Philipp Cimiano , Siegfried Handschuh , Steffen Staab, Towards the self-annotating web, Proceedings of the 13th international conference on World Wide Web, May 17-20, 2004, New York, NY, USA [doi>10.1145/988672.988735]
• 6: Philipp Cimiano , Günter Ladwig , Steffen Staab, Gimme' the context: context-driven automatic semantic annotation with C-PANKOW, Proceedings of the 14th international conference on World Wide Web, May 10-14, 2005, Chiba, Japan [doi>10.1145/1060745.1060796]
• 7: Nigel Collier , Chikashi Nobata , Jun-ichi Tsujii, Extracting the names of genes and gene products with a hidden Markov model, Proceedings of the 18th conference on Computational linguistics, p.201-207, July 31-August 04, 2000, Saarbrücken, Germany [doi>10.3115/990820.990850]
• 8: Stephen Dill , Nadav Eiron , David Gibson , Daniel Gruhl , R. Guha , Anant Jhingran , Tapas Kanungo , Sridhar Rajagopalan , Andrew Tomkins , John A. Tomlin , Jason Y. Zien, SemTag and seeker: bootstrapping the semantic web via automated semantic annotation, Proceedings of the 12th international conference on World Wide Web, May 20-24, 2003, Budapest, Hungary [doi>10.1145/775152.775178]
• 9: Etzioni, O., Cafarella, M. J., Downey, D., Popescu, A.-M., Shaked, T., Soderland, S., Weld, D. S., and Yates, A. 2004. Methods for domain-independent information extraction from the web: An experimental comparison. In Proceedings of the National Conference on Artificial Intellegence, D. L. McGuinness and G. Ferguson, Eds. The MIT Press, 391--398.
• 10: Fukuda, K., Tsunoda, T., Tamura, A., and Takagi, T. 1998. Toward information extraction: Identifying protein names from biological papers. In Proceedings of the Pacific Symposium on Biocomputing (PBS'98).
• 11: Roxana Girju , Dan I. Moldovan, Text Mining for Causal Relations, Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference, p.360-364, May 14-16, 2002
• 12: R. Guha , Rob McCool, TAP: a Semantic Web platform, Computer Networks: The International Journal of Computer and Telecommunications Networking, v.42 n.5, p.557-577, 05 August 2003 [doi>10.1016/S1389-1286(03)00225-1]
• 13: Marti A. Hearst, Automatic acquisition of hyponyms from large text corpora, Proceedings of the 14th conference on Computational linguistics, August 23-28, 1992, Nantes, France [doi>10.3115/992133.992154]
• 14: Lee, B., Hendler, T., and Lassila, J. 2001. The semantic web. Scientific Amer.
• 15: McDonald, R. 2005. Extracting relations from unstructured text. Tech. rep., Department of Computer and Information Science, University of Pennsylvania.
• 16: Mukherjea, S. and Sahay, S. 2006. Discovering biomedical relations utilizing the World Wide Web. In Proceedings of the Pacific Symposium on Biocomputing, R. B. Altman, T. Murray, T. E. Klein, A. K. Dunker, and L. Hunter, Eds. World Scientific, 164--175.
• 17: L. Venkata Subramaniam , Sougata Mukherjea , Pankaj Kankar , Biplav Srivastava , Vishal S. Batra , Pasumarti V. Kamesam , Ravi Kothari, Information extraction from biomedical literature: methodology, evaluation and an application, Proceedings of the twelfth international conference on Information and knowledge management, November 03-08, 2003, New Orleans, LA, USA [doi>10.1145/956863.956941]
• 18: Wong, L. 2001. Pies, a protein interaction extraction system. In Proceedings of the Pacific Symposium on Biocomputing, R. B. Altman, A. K. Dunker, L. Hunter, and T. E. Klein, Eds. Vol. 6. World Scientific, 520--531.
• 19: Dmitry Zelenko , Chinatsu Aone , Anthony Richardella, Kernel methods for relation extraction, The Journal of Machine Learning Research, 3, 3/1/2003

INDEX TERMS

Primary Classification:
  J. Computer Applications
  J.3 LIFE AND MEDICAL SCIENCES
      Subjects: Medical information systems

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing
          Subjects: Linguistic processing

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.7 Natural Language Processing
          Subjects: Language parsing and understanding

General Terms:
Algorithms, Experimentation, Languages

Keywords:
Ontology construction, relation identification