Data processing: speech signal processing – linguistics – language – Linguistics – Natural language
Reexamination Certificate
2006-12-05
2006-12-05
Dorvil, Richemond (Department: 2626)
Data processing: speech signal processing, linguistics, language
Linguistics
Natural language
C704S004000, C704S010000
Reexamination Certificate
active
07146308
ABSTRACT:
The present invention provides a facility for discovering a set of inference rules, such as “X is author of Y≈X wrote Y”, “X solved Y≈X found a solution to Y”, and “X caused Y≈Y is triggered by X”, by analyzing a corpus of natural language text. The corpus is parsed to identify grammatical relationships between words and to build dependency trees formed of the relationships between the words. Paths linking words in the dependency trees are identified. If two paths tend to link the same sets of words, their meanings are taken to be similar. An inference rule is generated for each pair of similar paths. The output of the inventive system is a set of inference rules and a database in which to store these inference rules. The rules generated by the system are interpretable by machines and used in other applications (e.g. information extraction, information retrieval, and machine translation).
REFERENCES:
patent: 5289376 (1994-02-01), Yokogawa
patent: 5424947 (1995-06-01), Nagao et al.
patent: 5926784 (1999-07-01), Richardson et al.
patent: 5937385 (1999-08-01), Zadrozny et al.
patent: 5991712 (1999-11-01), Martin
patent: 5995918 (1999-11-01), Kendall et al.
patent: 6161084 (2000-12-01), Messerly et al.
Fraser et al. Inheritence in Word Grammar, 1992, Association for Computer Linguistics, pp. 133-158.
Delugach et al. Wizard: A Database Inference Analysis and Detection System, Feb. 1996, IEEE Transactions On Data and Knowledge Engineering, vol. 8, No. 1, pp. 56-66.
Richardson et al. MindNet: Acquiring and structuring semantic information from text, May 1998, Association for Computational Linguistics, pp. 1098-1102.
“Fast and Effective Text Mining Using Linear-time Documents Clustering”, Bjornar Larson and Chinatsu Aone, KDD-99 San Diego, California, United States, Copyright ACM 1999 1-58113-143-7/99/08, pp. 16-22.
“Text Mining: Natural Language techniques and Text Mining applications”, M. Rajman and R. Besançon, Chapman & Hall, IFIP 1997, pp. 2-15.
“Extracting Classification Knowledge of Internet Documents with Mining Term Associations: A Semantic Approach”, Shian-Hua Lin, Chi-Sheng Shih, Meng Chang Chen, Jan-Ming Ho, Ming-Tat Ko and Yueh-Ming Huang, SIGIR'98, Melbourne, Australia, Copyright 1998 ACM 1-58113-015-5 Aug. 1998, pp. 241-249.
“Automatic Acquisition of Hyponyms from Large Text Corpora”, Marti A. Hearst, Proceedings of the Fourteenth International Conference on Computational Linguistics, Nantes, France, Jul. 1992, 8 pages.
“Automatic Search Term Variant Generation”, K. Sparck Jones and J.I. Tait,Journal of Documentation,vol. 40, No. 1, Mar. 1984, pp. 50-66.
“Boosting Variant Recognition with Light Semantics”, Cécile Fabre and Christian Jacquemin, Cooling-2000, Saarbrucken, Germany, Aug. 2000, pp. 264-270.
“Principle-Based Parsing Without Overgeneration”, Dekang Lin, in proceedings of ACL-93, Columbus, Ohio, Jun. 1993, pp. 112-120.
“English for the Computer: The SUSANNE Corpus and Analytic Scheme”, Geoffrey Sampson, Clarendon Press, Oxford, 1995, pp. 1-11.
“A New Statistical Parser Based on Bigram Lexical Dependencies”, Michael John Collins, cmp-lg/9605012 May 6, 1996, 4 pages (double sided).
“A Maximum-Entropy-Inspired Parser”, Eugene Charniak, in proceedings of the First North American Chapter of ACL, Seattle, Washington, Apr. 2000, pp. 132-139.
“Distributional Structure”, Z. Harris, fromWord10 No. 2-3 (1954) pp. 775-793 and notes, pp. 26-47.
“Extracting Collocations from Text Corpora”, Dekang Lin, in proceedings of the Workshop on Computational Terminology, Montreal, Canada, Aug. 1998, pp. 57-63.
“Thesaurus Construction”, Padmini Srinivasan,Information retrieval Data Structures and Algorithms,Chapter 9, eds. Frakes, W.B. and Baeza-Yates R., Prentice Hall, 1992, pp. 161-176.
“Efficient Clustering of High-Dimensional Data Sets with Application to Reference Matching”, Andrew McCallum, Kamal Nigam and Lyle H. Unger, KDD 2000, Boston, MA, United States, Copyright ACM, Aug. 2000 1-58113-233-6/00/08, pp. 169-178.
Lin Dekang
Pantel Patrick
Dorvil Richemond
Shortledge Thomas E.
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