Autonomous document classification for business

Subscribe (Full Service)


	Search: The ACM Digital Library The Guide

	Feedback

Autonomous document classification for business

Full text

Pdf (572 KB)

Source

International Conference on Autonomous Agents archive
Proceedings of the first international conference on Autonomous agents table of contents

Marina del Rey, California, United States

Pages: 201 - 208

Year of Publication: 1997

ISBN:0-89791-877-0

Authors

Chris Clack	Dept. Computer Science, University College London, Gower Street, London WC1E 6BT
Johnny Farringdon	Dept. Computer Science, University College London, Gower Street, London WC1E 6BT
Peter Lidwell	University College London, c/o Friends of the Earth, 26-28 Underwood Street, London N1 7JQ
Tina Yu	Dept. Computer Science, University College London, Gower Street, London WC1E 6BT

Sponsors

SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 7, Downloads (12 Months): 25, Citation Count: 6

Additional Information:

references cited by index terms collaborative colleagues

Tools and Actions:	Review this Article Save this Article to a Binder Display Formats: BibTeX EndNote ACM Ref

DOI Bookmark:	Use this link to bookmark this Article: http://doi.acm.org/10.1145/267658.267716 What is a DOI?

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	Nicholas J. Belkin , W. Bruce Croft, Information filtering and information retrieval: two sides of the same coin?, Communications of the ACM, v.35 n.12, p.29-38, Dec. 1992 [doi>10.1145/138859.138861]
	2	Clack, C., Farringdon, J., Lidwell, P., Yu, T. 1996. An Adaptive Document Classification Agent, Research note, RN/96/45, Dept. of Computer Science, University College London.
	3	Clack, C., Yu, T. 1996. Performance-Enhanced Genetic Programming, Research note, RN/96/116, Dept. Computer Science, University College London.
	4	Deerwester, S.,Dumais, S.T., Furnas, G.W., Landaver, J.K., Harshman R. 1990. Indexing by Latent Semantic Analysis. Journal of the American Society for Information Science, Vol. 41, No 6, 391-407.
	5	Farringdon, J. 1996a. Genetic Programming Science, Internal note, IN/96/05, Dept. of Computer Science, University College London.
	6	Farringdon, J. 1996b. Natural Feedback for Autonomous Agents, Internal note, IN/96/07, Dept. of Computer Science, University College London.
	7	S. Gauch , J. B. Smith, An expert system for searching in full-text, Information Processing and Management: an International Journal, v.25 n.3, p.253-263, May 1989 [doi>10.1016/0306-4573(89)90043-5]
	8	General Magic, 1996. URL: http://www.genmagic.com/
	9	John R. Koza , James P. Rice, Genetic programming (videotape): the movie, MIT Press, Cambridge, MA, 1992
	10	Lang, K. 1995. NewsWeeder, Learning to Filter Nemews. In Proceedings of the 12th International Machine Learning Conference (ML95), pp. 331-339, San Francisco, CA:Morgan Kaufman.
	11	Marcus, R.S. 1991. Computer and Human Understanding in Intelligent Retrieval Assistance. Proceedings of the 54th American Society for Information Science meeting, Vol. 28, October, pp. 49-59.
	12	Metral, M. 1993. Design of a Genetic Learning interface Agent. BSc Thesis, Department of Electrical Engineering & Computer Science, MIT.
	13	Payne, T. 1994. Learning E-mail Filtering Rules with Magi, A Mail Agent Interface. MSc Thesis, Department of Computing Science, University of Aberdeen Scotland.
	14	Quinlan, P.T. 1992. Oxford Psycholinguistic Daiabase.
	15	Gerard Salton , Michael J. McGill, Introduction to Modern Information Retrieval, McGraw-Hill, Inc., New York, NY, 1986
	16	Sheth, B. 1994. A learning Approach to Personalised Information Filtering. Masters Thesis, Department of Electrical Engineering & Computer Science, MIT.

CITED BY 6

	Fabrizio Sebastiani, Machine learning in automated text categorization, ACM Computing Surveys (CSUR), v.34 n.1, p.1-47, March 2002
	Stephane Zrehen , Michael A. Arbib, Understanding jokes: a neural approach to content-based information retrieval, Proceedings of the second international conference on Autonomous agents, p.343-349, May 10-13, 1998, Minneapolis, Minnesota, United States
	Gary Boone, Concept features in Re:Agent, an intelligent Email agent, Proceedings of the second international conference on Autonomous agents, p.141-148, May 10-13, 1998, Minneapolis, Minnesota, United States
	Baoping Zhang , Yuxin Chen , Weiguo Fan , Edward A. Fox , Marcos Gonçalves , Marco Cristo , Pável Calado, Intelligent GP fusion from multiple sources for text classification, Proceedings of the 14th ACM international conference on Information and knowledge management, October 31-November 05, 2005, Bremen, Germany
	Laurence Hirsch , Robin Hirsch , Masoud Saeedi, Evolving Lucene search queries for text classification, Proceedings of the 9th annual conference on Genetic and evolutionary computation, July 07-11, 2007, London, England
	Yakup Yildirim , Turgay Yilmaz , Adnan Yazici, Ontology-supported object and event extraction with a genetic algorithms approach for object classification, Proceedings of the 6th ACM international conference on Image and video retrieval, p.202-209, July 09-11, 2007, Amsterdam, The Netherlands