Post-supervised template induction for information extraction from lists and tables in dynamic web sources

Journal of Intelligent Information Systems

Volumn 25, Issue 1, 2005, Pages 69-93

  Shi, Z ^a   Milios, E ^a   Zincir Heywood, N ^a  

^a DALHOUSIE UNIVERSITY   (Canada)

Author keywords

Grammar induction; Information extraction; Template induction; Unsupervised learning

Indexed keywords

ALGORITHMS; HTML; LEARNING SYSTEMS; USER INTERFACES; WEBSITES;

GRAMMAR INDUCTION; INFORMATION EXTRACTION; TEMPLATE INDUCTION; UNSUPERVISED LEARNING;

INFORMATION ANALYSIS;

EID: 23944442806     PISSN: 09259902     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10844-005-0861-z     Document Type: Article

References (27)

1. Carrasco, R. and Oncina, J. (1994). Learning Stochastic Regular Grammars by Means of a State Merging Method. In Proceedings of the Second International Colloquium on Grammatical Inference and Applications (ICGI94), volume 862 of Lecture Notes on Artificial Intelligence, (pp. 139-152). Berlin, Springer Verlag.
2. Cheeseman, P. and Stutz, J. (1996). Bayesian Classification (AUTOCLASS): Theory and Results. Advances in Knowledge Discovery and Data Mining (pp. 153-180). AAAI/MIT Press.
3. Cohen, W. and Jensen, L. (2001). A Structured Wrapper Induction System for Extracting Information from Semi-Structured Documents. In Automatic Text Extraction and Mining workshop (ATEM-01), IJCAI-01, Seattle, WA, USA.
4. Cormen, T., Leiserson, C., and Rivest, R. (1989). Introduction to Algorithms. Cambridge, Massachusetts: MIT Press.
5. Degroot, M. and Schervish, M. (1975). Probability and Statistics. Cambridge, Massachusetts: Addison-Wesley Pub. Co.
6. Deitel, H., Deitel, P., and Nieto, T. (2000). Internet and World Wide Web: How to Program. Upper Saddle River, NJ 07458: Prentice-Hall.
7. Freitag, Dayne and McCallum, Andrew. (2000). Information Extraction with HMM Structures Learned by Stochastic Optimization. In AAAI/IAAI, (pp. 584-589).
8. Hanson, J., Stutz, R., and Cheeseman, P. (1991). Bayesian Classification Theory. Technical report, NASA Ames TR FIA-90-12-7-01.
9. Hearst, M. (1998). Information Integration. IEEE Intelligent Systems, 13(5), 12-16.
10. Knoblock, C., Lerman, K., Minton, S., and Muslea, I. (2001). A Machine Learning Approach to Accurately and Reliably Extracting Data from the Web. In IJCAI-2001 Workshop on Text Learning: Beyond Supervision, Seattle, WA, USA.
11. Kushmerick, N. (1997). Wrapper Induction for Information Extraction. Technical report, Dept. of Computer Science, U. of Washington, TR UW-CSE-97-11-04.
12. Kushmerick, N. (2000). Wrapper Induction: Efficiency and Expressiveness. Artificial Intelligence, 118: 15-68.
13. Lerman, K., Knoblock, C., and Minton, S. (2001). Automatic Data Extraction from Lists and Tables in Web Sources. In Automatic Text Extraction and Mining workshop (ATEM-01), IJCAI-01. Seattle, WA, USA.
14. Lerman, K. and Minton, S. (2000). Learning the Common Structure of Data. In In Proceedings of the 17th National Conference on Artificial Intelligence (AAAI-2000), AAAI Press (pp. 609-614). Menlo Park.
15. Lewis, H. and Papadimitriou, C. (1998). Elements of the Theory of Computation. Upper Saddle River, NJ 07458: Prentice-Hall.
16. Liang, J., Milios, E., and Zincir-Heywood, N. (2002). A Robot Capable of Crawling Secure Dynamic Web Sites. Technical Report, Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada.
17. McCallum, Andrew, Freitag, Dayne, and Pereira, Fernando. (2000). Maximum Entropy Markov Models for Information Extraction and Segmentation. In Proc. 17th International Conf. on Machine Learning (pp. 591-598). Morgan Kaufmann, San Francisco, CA.
18. Muslea, I., Minton, S., and Knoblock, C. (2001). Hierarchical Wrapper Induction for Semistructured Information Sources. Journal of Autonomous Agents and Multi-Agent Systems, 4: 93-114.
19. Ng, H., Lim, C., and Koo, J. (1999). Learning to Recognize Tables in Free Text. In Proceedings of the 37th Annual Meeting of ACL (pp. 443-450).
20. Pinto, D., McCallum, A., Lee, X., and Croft, W. 2003. Table Extraction Using Conditional Random Fields. In Proceedings of the 26th ACM SIGIR.
21. Pinto, David, McCallum, Andrew, Wei, Xing, and Bruce Croft, W. (2003). Table Extraction Using Conditional Random Fields. In Proceedings of the ACM SIGIR.
22. Pyreddy, Pallavi and Bruce Croft, W. (1997). TINTIN: A System for Retrieval in Text Tables. In ACM DL, (pp. 193-200).
23. Shi, Z., Milios, E.,and Zincir-Heywood, N. (2002). Post-Supervised Template Induction for Information Extraction From Lists and Tables in Dynamic Web Sources. Technical Report CS-2002-09, Dalhousie University, Faculty of Computer Science.
24. Weisstein, Eric W. (2005). "Variation Coefficient." From MathWorld - A Wolfram Web Resource. http://mathworld.wolfram.com/VariationCoefficient.html, Accessed on Apr. 15, 2005.
25. http://www.borders.com/. (2001). Amazon online shopping site. Accessed on November 12, 2001.
26. http://www.travelocity.com/. (2002). Travelocity travel site. Accessed on Oct. 23, 2002.
27. http://www.whitepages.com/. (2002). WhitePages online directory service. Accessed on Oct. 23, 2002.