Unsupervised information extraction from unstructured, ungrammatical data sources on the World Wide Web

International Journal on Document Analysis and Recognition

Volumn 10, Issue 3-4, 2007, Pages 211-226

  Michelson, Matthew ^a   Knoblock, Craig A ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

Information extraction; Information integration; Semantic annotation; Unstructured data sources; Unsupervised

Indexed keywords

DATA PROCESSING; INFORMATION ANALYSIS; SEMANTICS; SUPERVISED LEARNING;

INFORMATION EXTRACTION; INFORMATION INTEGRATION; SEMANTIC ANNOTATION; UNSTRUCTURED DATA SOURCES; UNSUPERVISED EXTRACTION;

WORLD WIDE WEB;

EID: 37249020884     PISSN: 14332833     EISSN: 14332825     Source Type: Journal    
DOI: 10.1007/s10032-007-0052-2     Document Type: Conference Paper

References (25)

1. Agichtein, E., Ganti, V.: Mining reference tables for automatic text segmentation. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 20-29. ACM, Baltimore (2004)
2. Bilenko, M., Mooney, R.J.: Adaptive duplicate detection using learnable string similarity measures. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 39-48. ACM, Baltimore (2003)
3. Cafarella, M.J., Downey, D., Soderland, S., Etzioni, O.: KnowItNow: Fast, scalable information extraction from the web. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 563-570. Association for Computational Linguistics, East Stroudsburg (2005)
4. Carman, M.J., Knoblock, C.A.: Learning semantic descriptions of web information sources. In: Proceedings of the International Joint Conference on Artificial Intelligence, pp. 2695-2700 (2007)
5. Ciravegna, F.: Adaptive information extraction from text by rule induction and generalisation. In: Proceedings of the International Joint Conference on Artificial Intelligence, pp. 1251-1256 (2001)
6. Cohen, W., Ravikumar, P., Feinberg, S.: A comparison of string metrics for matching names and records. In: Proceedings of the ACM SIGKDD Workshop on Data Cleaning, Record Linkage, and Object Consolidation, pp. 13-18 (2003)
7. Cohen, W., Sarawagi, S.: Exploiting dictionaries in named entity extraction: Combining semi-markov extraction processes and data integration methods. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 89-98. ACM, Baltimore (2004)
8. Craswell, N., Bailey, P., Hawking, D.: Server selection on the world wide web. In: Proceedings of the Conference on Digital Libraries, pp. 37-46. ACM, Baltimore (2000)
9. Dill, S., Gibson, N., Gruhl, D., Guha, R., Jhingran, A., Kanungo, T., Rajagopalan, S., Tomkins, A., Tomlin, J.A., Zien, J.Y.: Semtag and seeker: Bootstrapping the semantic web via automated semantic annotation. In: Proceedings of the International World Wide Web Conference, pp. 178-186. ACM, Baltimore (2003)
10. Hassan, H., Hassan, A., Emam, O.: Unsupervised information extraction approach using graph mutual reinforcement. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 501-508. Association for Computational Linguistics, East Stroudsburg (2006)
11. Kushmerick, N., Weld, D.S., Doorenbos, R.: Wrapper induction for information extraction. In: Proceedings of the International Joint Conference on Artificial Intelligence, pp. 729-737 (1997)
12. Lerman, K., Plangrasopchok, A., Knoblock, C.A.: Automatically labeling the inputs and outputs of web services. In: Proceedings of the National Conference on Artificial Intelligence, pp. 1363-1368. AAAI, Charlotte (2006)
13. Levy, A.: Logic-based techniques in data integration. In: J. Minker (ed.) Logic Based Artificial Intelligence, pp. 575-595. Kluwer, Dordrecht (2000)
14. Levy, A.Y., Rajaraman, A., Ordille, J.J.: Querying heterogeneous information sources using source descriptions. In: Proceedings of the International Conference on Very Large Data Bases, pp. 251-262. Morgan Kaufmann, San Fransisco (1996)
15. Lin J. (1991). Divergence measures based on the shannon entropy. IEEE Trans. Inf. Theory 37(1): 145-151
16. McCallum, A.: Mallet: A machine learning for language toolkit http:// mallet.cs.umass.edu (2002)
17. Michelson, M., Knoblock, C.A.: Semantic annotation of unstructured and ungrammatical text. In: Proceedings of the International Joint Conference on Artificial Intelligence, pp. 1091-1098 (2005)
18. Michelson, M., Knoblock, C.A.: An automatic approach to semantic annotation of unstructured, ungrammatical sources: A first look. In: Proceedings of the IJCAI Workshop on Analytics for Noisy Unstructured Text Data, pp. 123-130 (2007)
19. Michelson, M., Knoblock, C.A.: Mining heterogeneous transformations for record linkage. In: Proceedings of the International Workshop on Information Integration on the Web, pp. 68-73. AAAI, Charlotte (2007)
20. Minton, S.N., Nanjo, C., Knoblock, C.A., Michalowski, M., Michelson, M.: A heterogeneous field matching method for record linkage. In: Proceedings of the IEEE International Conference on Data Mining, pp. 314-321. IEEE Computer Society, Washington DC (2005)
21. Paşca, M., Lin, D., Bigham, J., Lifchits, A., Jain, A.: Organizing and searching the world wide web of facts - step one: The one - million fact extraction challenge. In: Proceedings of the National Conference on Artificial Intelligence, pp. 1400-1405. AAAI, Charlotte (2006)
22. Reeve, L., Han, H.: Survey of semantic annotation platforms. In: Proceedings of ACM Symposium on Applied Computing, pp. 1634-1638. ACM, Baltimore (2005)
23. Smith T.F., Waterman M.S. (1981). Identification of common molecular subsequences. J. Mol. Biol. 147: 195-197
24. Thakkar S., Ambite J.L., Knoblock C.A. (2005). Composing, optimizing, and executing plans for bioinformatics web services. Int. J. Very Large Databases, Spec. Issue Data Manage. Anal. Mining Life Sci 14(3): 330-353
25. Winkler, W.E.: The state of record linkage and current research problems. Technical Report U.S. Census Bureau (1999)