Information forage through adaptive visualization

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Information forage through adaptive visualization

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International Conference on Digital Libraries archive
Proceedings of the third ACM conference on Digital libraries table of contents

Pittsburgh, Pennsylvania, United States

Pages: 303 - 304

Year of Publication: 1998

ISBN:0-89791-965-3

Authors

Dmitri Roussinov	Department of MIS, University of Arizona, McClelland Hall 430, Tucson, AZ
Marshall Ramsey	Department of MIS, University of Arizona, McClelland Hall 430, Tucson, AZ

Sponsors

SIGIR: ACM Special Interest Group on Information Retrieval
SIGLINK: Hypertext, Hypermedia, and Web
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 3, Downloads (12 Months): 34, Citation Count: 5

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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	John M. Carroll , John M. Thomas, FUN, ACM SIGCHI Bulletin, v.19 n.3, p.21-24, January 1988 [doi>10.1145/49108.1045604]
	2	Chen H., Schuffels C., and Orwig R., internet Categorization and Search: A Self-Organizing Approach. Journal of Visual Communications and Image Representation, Vol. 7. No. 1. March. pp.88-102, 1996.
	3	James W. Cooper , Roy J. Byrd, Lexical navigation: visually prompted query expansion and refinement, Proceedings of the second ACM international conference on Digital libraries, p.237-246, July 23-26, 1997, Philadelphia, Pennsylvania, United States [doi>10.1145/263690.263828]
	4	Marti A. Hearst , Jan O. Pedersen, Reexamining the cluster hypothesis: scatter/gather on retrieval results, Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval, p.76-84, August 18-22, 1996, Zurich, Switzerland [doi>10.1145/243199.243216]
	5	Teuvo Kohonen, Self-organizing maps, Springer-Verlag New York, Inc., Secaucus, NJ, 1997
	6	Roussinov D. and Chert H. A Scalable Self-organizing Map Algorithm for Textual Classification: A Neural Network Approach to Thesaurus Generation, Communication Cognition and Artificial Intelligence, Spring 1998.
	7	G. Salton , A. Wong , C. S. Yang, A vector space model for automatic indexing, Communications of the ACM, v.18 n.11, p.613-620, Nov. 1975 [doi>10.1145/361219.361220]

CITED BY 5

	G. Benoît, Data discretization for novel relationship discovery in information retrieval, Journal of the American Society for Information Science and Technology, v.53 n.9, p.736-746, August 2002
	Dieter Merkl, Industry: text mining with self-organizing maps, Handbook of data mining and knowledge discovery, Oxford University Press, Inc., New York, NY, 2002
	Erich Schweighofer , Dieter Merkl, A learning technique for legal document analysis, Proceedings of the 7th international conference on Artificial intelligence and law, p.156-163, June 14-17, 1999, Oslo, Norway
	Krista Lagus , Samuel Kaski , Teuvo Kohonen, Mining massive document collections by the WEBSOM method, Information Sciences: an International Journal, v.163 n.1-3, p.135-156, 14 June 2004
	Ozgur Turetken , Ramesh Sharda, Visualization of web spaces: state of the art and future directions, ACM SIGMIS Database, v.38 n.3, August 2007