Information retrieval based on context distance and morphology

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Information retrieval based on context distance and morphology

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Annual ACM Conference on Research and Development in Information Retrieval archive
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval table of contents

Berkeley, California, United States

Pages: 90 - 96

Year of Publication: 1999

ISBN:1-58113-096-1

Authors

Hongyan Jing	Department of Computer Science, Columbia University, New York, NY
Evelyne Tzoukermann	Bell Laboratories - Lucent Technologies, 700 Mountain Ave., Murray Hill, NJ

Sponsor

SIGIR: ACM Special Interest Group on Information Retrieval

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 9, Downloads (12 Months): 58, Citation Count: 7

Additional Information:

references cited by index terms collaborative colleagues peer to peer

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Chris Buckley, Gerard Salton, James Allan, and Amit Singhal. 1994a. Automatic query expansion using smart: Trec 3. In Proceedings of The third Text RE- trieval Conference (TREC-3), Gaithersburg, Maryland.
	2	Chris Buckley, Gerard Salton, James Allan, and Amit Singhal. 1994b. Automatic query expansion using smart: Trec 3. In Proceedings of The third Text RE- trieval Conference (TREC-3), Gaithersburg, Maryland.
	3	CELEX. 1995. The CELEX lexical database--Dutch, English, German. CD-ROM. Centre for Lexical Information, Max Planck Institute for Psycholinguistics, Nijmegen.
	4	Kenneth Ward Church, One term or two?, Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval, p.310-318, July 09-13, 1995, Seattle, Washington, United States [doi>10.1145/215206.215376]
	5	Scott Deerwester, Susan T. Dumais, George Furnas, Thomas K. Landauer, and Richard Harshman. 1990. Indexing by latent semantic analysis. Jourhal of the American Society for Information Science, 41(6):391 407.
	6	William A. Gale , Kenneth W. Church , David Yarowsky, One sense per discourse, Proceedings of the workshop on Speech and Natural Language, February 23-26, 1992, Harriman, New York [doi>10.3115/1075527.1075579]
	7	David A. Hull, Stemming algorithms: a case study for detailed evaluation, Journal of the American Society for Information Science, v.47 n.1, p.70-84, Jan. 1996 [doi>10.1002/(SICI)1097-4571(199601)47:1<70::AID-ASI7>3.3.CO;2-Q]
	8	Adam Kilgarriff. 1993. Dictionary word sense distinctions: An enquiry into their nature. In Computers and the Humanities, volume 26:365-387.
	9	Robert Krovetz, Viewing morphology as an inference process, Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval, p.191-202, June 27-July 01, 1993, Pittsburgh, Pennsylvania, United States [doi>10.1145/160688.160718]
	10	Huang Li and Naoki Abe. 1998. Word clustering and disambiguation based on co-occurrence data. pages 749-755, Montreal, Canada.
	11	Julie Beth Lovins. 1968. Development of a stemming algorithm. Translation and Computational Linguistics, 11(1):22-31.
	12	Susan W. McRoy, Using multiple knowledge sources for word sense discrimination, Computational Linguistics, v.18 n.1, p.1-30, March 1992
	13	Hwee Tou Ng , Hian Beng Lee, Integrating multiple knowledge sources to disambiguate word sense: an exemplar-based approach, Proceedings of the 34th annual meeting on Association for Computational Linguistics, p.40-47, June 24-27, 1996, Santa Cruz, California [doi>10.3115/981863.981869]
	14	M. F. Porter. 1980. An algorithm for suffix stripping. Program, 14:130-137.
	15	Hinrich Sch/itze and Jan O. Pedersen. 1995. Information retrieval based on word senses. In Symposium on Document Analysis and Information Retrieval (SDAIR), Las Vegas, NV. University of Nevada.
	16	Hinrich Schütze, Automatic word sense discrimination, Computational Linguistics, v.24 n.1, March 1998
	17	Jinxi Xu , W. Bruce Croft, Query expansion using local and global document analysis, Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval, p.4-11, August 18-22, 1996, Zurich, Switzerland [doi>10.1145/243199.243202]
	18	David Yarowsky. 1992. Word-sense disambiguation using statistical models of roget's thesaurus categories trained on a large corpus.

CITED BY 7

	Andrey L. Gorbunov, Relevance of web documents: ghosts consensus method, Journal of the American Society for Information Science and Technology, v.53 n.10, p.783-788, August 2002
	Jimin Liu , Tat-Seng Chua, Building semantic perceptron net for topic spotting, Proceedings of the 39th Annual Meeting on Association for Computational Linguistics, p.378-385, July 06-11, 2001, Toulouse, France
	Holger Billhardt , Daniel Borrajo , Victor Maojo, A context vector model for information retrieval, Journal of the American Society for Information Science and Technology, v.53 n.3, p.236-249, February 1 2002
	Hervé Stoppiglia , Gérard Dreyfus , Rémi Dubois , Yacine Oussar, Ranking a random feature for variable and feature selection, The Journal of Machine Learning Research, 3, 3/1/2003
	Hong-Ding Wang , Yun-Hai Tong , Shao-Hua Tan , Shi-Wei Tang , Dong-Qing Yang , Guo-Hui Sun, An adaptive approach to schema classification for data warehouse modeling, Journal of Computer Science and Technology, v.22 n.2, p.252-260, March 2007
	Raymond Y. K. Lau, Context-sensitive text mining and belief revision for intelligent information retrieval on the web, Web Intelligence and Agent System, v.1 n.3,4, p.151-172, December 2003
	Raymond Y. K. Lau, Context-sensitive text mining and belief revision for intelligent information retrieval on the web, Web Intelligence and Agent System, v.1 n.3-4, p.151-172, March 2003

INDEX TERMS

Primary Classification:
H. Information Systems
H.3 INFORMATION STORAGE AND RETRIEVAL
H.3.3 Information Search and Retrieval
Subjects: Retrieval models

Additional Classification:
I. Computing Methodologies
I.2 ARTIFICIAL INTELLIGENCE
I.7 DOCUMENT AND TEXT PROCESSING

General Terms:
Algorithms, Design, Documentation, Experimentation, Management, Measurement, Performance, Theory

Collaborative Colleagues:

Hongyan Jing: colleagues

Evelyne Tzoukermann: colleagues

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