Retrieving NASA problem reports: A case study in natural language information retrieval

Data and Knowledge Engineering

Volumn 48, Issue 2, 2004, Pages 231-246

  Van Delden, Sebastian ^a   Gomez, Fernando ^a  

^a University of Central Florida   (United States)

Author keywords

Finite state; Information retrieval; Natural language; Partial parsing

Indexed keywords

FINITE AUTOMATA; KNOWLEDGE BASED SYSTEMS; NATURAL LANGUAGE PROCESSING SYSTEMS; ONLINE SEARCHING; QUERY LANGUAGES; SEMANTICS; SET THEORY; SOFTWARE ENGINEERING; SPEECH PROCESSING;

NATURAL LANGUAGES; ONTOLOGIES; PARTIAL PARSING;

INFORMATION RETRIEVAL;

EID: 0346341050     PISSN: 0169023X     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0169-023X(03)00106-X     Document Type: Conference Paper

References (30)

1. S. Abney, Partial parsing via finite-state cascades, The ESSLLI'96 Robust Parsing Workshop, 1996.
2. Abney S. Tagging and partial parsing. Church K., Young S., Bloothooft G. Corpus-Based Methods in Language and Speech, An ELSNET Volume. 1996;Kluwer Academic Publishers, Dordrecht.
3. Abney S. Parsing by chunks. Berwick R., Abney S., Tenny C. Principle-Based Parsing. 1994;257-278 Kluwer Academic Publishers, Dordrecht.
4. R. Argarwel, L. Boggess, A simple but useful approach to conjunct identification, The 30th Annual Meeting of the ACL, 1992, pp. 15-21.
5. T. Brants, TnT - a statistical part-of-speech tagger, in: The Sixth Applied Natural Language Processing Conference, 2000.
6. Brill E. Transformation-based error-driven learning and natural language processing: a case study in part of speech tagging. Computational Linguistics. 21(4):1995;543-565.
7. E. Brill, A report of recent progress in transformation-based error-driven learning, ARPA Human Language Technology Workshop, 1994.
8. K. Chruch, A stochastic parts program and noun phrase parser for unrestricted text, in: The Second Conference on Applied Natural Language Processing, 1988, pp. 136-143.
9. D. Cutting, J. Kupiec, J. Pederson, P. Sibun, A practical part-of-speech tagger, in: The 3rd Conference of Applied Natural Language Processing, 1992, pp. 133-140.
10. W. Daelemans, J. Zavrel, MBT: a memory-based part-of-speech tagger-generator, in: E. Ejerhed, I. Dagan (Eds.), The Fourth Workshop on Very Large Corpora, Copenhagen, 1996, pp. 14-27.
11. S. van Delden, F. Gomez, Combining finite state automata and a greedy learning algorithm to determine the syntactic role of commas, in: Proceedings of the 14th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2002), Washington, D.C., 2002, pp. 293-301.
12. S. Delisle, S. Szpakowicz, Realistic parsing: practical solutions of difficult problems, The Pacific Association for Computational Linguistics, 1995.
13. Frakes W. Stemming Algorithms, Information Retrieval: Data Structures & Algorithms. 1992;Prentice Hall. pp. 131-160.
14. Garside R., Leech G., Sampson G. The Computational Analysis of English: A Corpus-Based Approach. 1987;Longman, London, New York.
15. GCIDE, The Collaborative International Dictionary of English Version 0.41., 1999.
16. F. Gomez, An algorithm for aspects of semantic interpretation using an enhanced WordNet, The North American Chapter of the Association of Computational Linguistics, June 2001, pp. 87-94.
17. F. Gomez, Linking WordNet verb classes to semantic interpretation, The COLING-ACL Workshop on the Usage of WordNet on NLP Systems, 1998, pp. 58-64.
18. J. Gonzalo, F. Verdejo, I. Chugur, J. Cigarrán, Indexing with WordNet synsets can improve text retrieval, ACL/COLING Workshop on Usage of WordNet for Natural Language Processing, 1998.
19. Greene B., Rubin G. Automatic Grammatical Tagging of English. 1971;Brown University, Providence.
20. H. van Halteren, J. Zavre, W. Daelemans, Improving data driven word class tagging by system combination, COLING-ACL, 1998.
21. V. Leffa, Clause processing in complex sentences, Language Resources and Evaluation-LREC, 1998.
22. Q. Ma, K. Uchimoto, M. Murata, H. Isahara, Elastic neural networks of part of speech tagging, in: IEEE-INNS International Joint Conference on Neural Networks, 1999, pp. 2991-2996.
23. Marcus M., Santorini B., Marcinkiewiecz M. Building a large annotated corpus for English. Computational Linguistics. 19(2):1993;313-330.
24. G. Miller, Introduction to WordNet: An On-line Lexical Database, Princeton, CSL Report 43, 1993.
25. G. Ngai, R. Florian, Transformation-based learning in the fast lane, North American Chapter of the Association for Computational Linguistics, 2001.
26. Resnik P. Semantic similarity in a taxonomy: an information-based measure and its application to problems of ambiguity in natural language. Journal of Artificial Intelligence. 11:1999;95-130.
27. Rumelhart D.E., Hilton G.E., Williams R.J. Learning internal representations by error propagation. Parallel Distributed Processing. 1:1986;318-362.
28. B. Santorini, Part-of-speech Tagging Guidelines for the Penn Treebank Project, 3rd Revision, 2nd Printing, 1995.
29. A. Smeaton, F. Kelly, R. O'Donnell, TREC-4 experiments at Dublin City University: thresholding posting lists, query expansion with WordNet and POS tagging of Spanish, in: Text Retrieval Conference, TREC-4, 1995.
30. M. Wynne, A Post-Editor's Guide to CLAWS7 Tagging, University of Lancaster, Bailrigg, Lancaster, England LA1 4YT, 1996.