Information extraction from blogs

Handbook of Research on Web Log Analysis

Volumn , Issue , 2008, Pages 469-487

  Moens, Marie Francine ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 79960191741     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4018/978-1-59904-974-8.ch023     Document Type: Chapter

References (39)

1. Angheluta, R. and Moens, M.-F., 2007, Cross-document entity tracking, In G. Amati, C. Carpineto & G. Romano (Eds.), Advances in Information Retrieval - 29th European Conference on IR Research ECIR - Lecture Notes in Computer Science 4425 (pp. 670-674), Berlin: Springer.
2. Berendt, B. and Hanser, C., 2007, Tags are not metadata, but "just more content" - to some people, In Proceedings of the International Conference on Weblogs and Social Media ICWSM (pp. 19-26), Omnipress.
3. Berg, T. et al., 2007, Names and faces, University of California Berkeley. Technical report.
4. Berger, A.D., Della Pietra, S.A. and Della Pietra, V.J., 1996, A maximum entropy approach to natural language processing, Computational Linguistics, 22(1), 39-71.
5. Bikel, D. M., Schwartz, R. and Weischedel, R.M., 1999, An algorithm that learns what's in a name, Machine Learning, 34, 211-231.
6. Blei, D., Bagnell, J. and McCallum, A., 2002, Learning with scope, with application to information extraction and classification, In Uncertainty in Artificial Intelligence: Proceedings of the Eighteenth Conference (UAI-2002) (pp. 53-60), San Francisco, CA: Morgan Kaufmann.
7. Boiy, E., Hens, P., Deschacht, K. and Moens, M.F., 2007, Automatic sentiment analysis of on-line text, In Proceedings of the 11th International Conference on Electronic Publishing, Openness in Digital Publishing: Awareness, Discovery & Access 2007, Vienna Austria.
8. Cardie, C. and Wagstaff, K., 1999, Noun phrase coreference as clustering, In Proceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (pp. 82-89), ACL.
9. Christianini, N. and Shawe-Taylor, J., 2000, An Introduction to Support Vector Machines and Other Kernel Based Learning Methods, Cambridge, UK: Cambridge University Press.
10. Collins, M. and Singer, Y., 1999, Unsupervised models for named entity classification, In Proceedings of Empirical Methods in Natural Language Processing (EMNLP), College Park, MD.
11. Cowie, J. and Lehnert, W., 1996, Information extraction, Communications of the ACM, 39 (1), 80-91.
12. th Annual International ACM SIGIR Conference on Research and Development of Information Retrieval (pp. 77-88), New York: ACM.
13. nd Annual Meeting of the Association for Computational Linguistics (pp. 424-430), East Stroudsburg, PA: ACL.
14. De Beer, J. and Moens, M.-F., 2007, A general solution of (hidden) text salting. Technical Report K.U.Leuven.
15. De Smet, W. and Moens, M.-F., 2007, Generating a topic hierarchy from dialect texts. In Proceedings of the 4th International Workshop on Text-based Information Retrieval (TIR-07), IEEE Computer Society.
16. th Annual Meeting of the Association for Computational Linguistics, East Stroudsburg: ACL.
17. Feng, D. and Hovy, E.D., 2006, Learning to detect conversation focus of threaded discussions, in Proceedings of the Human Language Technology / North American Association of Computational Linguistics conference (HLT-NAACL 2006), New York, NY.
18. Fillmore, C.J. and Baker, C.F., 2001, Frame semantics for text understanding, In Proceedings of WordNet and Other Lexical Resources Workshop.
19. Gildea, D. and Jurafsky, D., 2002, Automatic labeling of semantic roles. Computational Linguistics, 28(3), 245-288.
20. Glenisson, P., Glänzel, W., Janssens, F. and De Moor, B., 2005, Combining full text and bibliometric information in mapping scientific disciplines, Information Processing & Management, 41 (6), 1548-1572.
21. Golder, S. and Huberman, B.A., 2007, The structure of collaborative tagging systems, Journal of Information Science, 32 (2): 198-208.
22. Hobbs, J. H. et al., 1996, FASTUS: A cascaded finite-state transducer for extracting information from natural-language text, In Finite State Devices for Natural Language Processing, Cambridge MA: The MIT Press.
23. Jansche, M. and Abney, S.P., 2002, Information extraction from voicemail transcripts, In Proceedings of Empirical Methods in Natural Language Processing. East Stroudsburg, PA: ACL.
24. th International Conference on Machine Learning (pp. 282-289), San Francisco, CA: Morgan Kaufmann.
25. Li, X., Morie, P. and Roth, D., 2006, Identification and tracing of ambiguous names. In Proceedings of the Human Language Technology - North American Chapter of the Association for Computational Linguistics (pp. 17-24).
26. Mamou, J., Carmel, D. and Hoory R., 2006, Spoken document retrieval from call-center conversations, In Proceedings of Twenty-Ninth Annual International ACM SIGIR Conference on Research and Development of Information Retrieval (pp. 51-58), New York: ACM.
27. Mani, I., Pustejovsky, J. and Gaizauskas, R. (Eds.), 2005, The Language of Time: A Reader. Oxford University Press.
28. Minkov, E., Wang, R.C. and Cohen, W.W., 2004, Extracting personal names from emails, In Proceedings of the Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP) (pp. 443-450), East Stroudsburg, PA: ACL.
29. Minsky, M., 1975, A framework for representing knowledge, In P.H. Winston (Ed.), The Psychology of Computer Vision (pp. 211-277), New York: McGraw-Hill.
30. Moens, M.-F., 2006, Information Extraction: Algorithms and Prospects in a Retrieval Context (The Information Retrieval Series 21). New York: Springer.
31. Moens, M.-F., Boiy, E., Mochales Palau, R. and Reed, C., 2007, Automatic detection of arguments in legal texts. In Proceedings of the Eleventh International Conference on Artificial Intelligence and Law, New York: ACM.
32. Munteanu, D.S. and Marcu, D., 2006, Extracting parallel sub-sentential fragments from comparable corpora, In Proceedings of ACL-2006, Sydney, Australia (pp. 81-88).
33. Pearl, J., 1988, Probabilistic Reasoning in Intelligent Systems, Morgan-Kaufmann.
34. Rennie, J.D.M. and Jaakkola, T., 2005, Using term informativeness for named entity detection. In Proceedings of the Twenty-Eight Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 353-360), New York: ACM.
35. Riloff, E. and Lorenzen, J., 1999, Extraction-based text categorization: Generating domain-specific role relationships automatically, In T. Strzalkowski (Ed.), Natural Language Information Retrieval (pp. 167-196), Dordrecht, The Netherlands: Kluwer Academic Publishers.
36. Schank, R. C., 1975, Conceptual Information Processing, Amsterdam: North Holland.
37. Shanahan, G., Qu, Y. and Wiebe, J., 2006, Computing Attitude and Affect in Text: Theory and Applications (The Information Retrieval Series 20), Berlin: Springer.
38. Sood, S.C., Owsley, S., Hammond, K.J. and Birnbaum, L., 2007, TagAssist: Automatic tag suggestion for blog posts. In Proceedings of the International Conference on Weblogs and Social Media ICWSM 2007 (pp. 177-183), Omnipress.
39. Zhang, J., Shen, D., Zu, G., Jian, S., and Tan, C.L., 2004, Enhancing HMM-based biomedical named entity recognition by studying special phenomena, Journal of Biomedical Informatics, 37, 411-422.