Automatic generation of a matching function by genetic programming for effective information retrieval
Inhaltsverzeichnis
Referenz
W. Fan, M. Gordon, P. Pathak: Automatic generation of a matching function by genetic programming for effective information retrieval. in: America’s Conference on Information System, Milwaukee, USA, August 1999
DOI
Abstract
With the advent of the Internet, online resources are increasingly available. Many users choose popular search engines to perform an online search to satisfy their information need. However, these search engines tend to turn up many non-relevant documents, which make their retrieval precision very low. How to find appropriate ranking metrics to retrieve more relevant documents and fewer non-relevant documents for users remains a big challenge to the information retrieval community. In this paper, we propose a new framework that combines the merits of genetic programming and relevance feedback techniques to automatically generate and refine the matching functions used for document ranking. This approach overcomes the shortcoming of traditional ranking algorithms using a fixed ranking strategy. It also gives some new ideas and hints for information retrieval professionals.
Extended Abstract
Bibtex
@INPROCEEDINGS{Fan99automaticgeneration,
author = {Weiguo Fan and Michael D. Gordon and Praveen Pathak},
title = {Automatic generation of a matching function by genetic programming for effective information retrieval},
booktitle = {Proceedings of the 1999 Americas Conference on Information Systems},
year = {1999},
pages = {49--51}
url={http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1374&context=amcis1999 http://de.evo-art.org/index.php?title=Automatic_generation_of_a_matching_function_by_genetic_programming_for_effective_information_retrieval},
}
Used References
Gordon, M. D. & Pathak, P. “Finding information on the WWW: Retrieval effectiveness of search engines”, Information Processing and Management, (To Appear).
Koza, J. R. “Genetic Programming: On the Programming of Computers by Means of Natural Selection”, MIT Press, Cambridge, MA, USA, 1992.
Pathak, P. “A Simulation model of document information retrieval system with relevance feedback”, Proceedings of the Fourth Americas Conference on Information Systems, Baltimore, 1998.
Salton, G. “Automatic Text Processing”, Addison- Wesley Publishing Co., Reading, MA, 1989.
Salton, G. & Buckley, C. “Term-weighting approaches in automatic text retrieval”, Information Processing and Management, 24(5), 1988, pp:513–523.
Salton G. & Buckley, C. “Improving Retrieval performance by relevance feedback”, Journal of American Society for Information Science, 41(4), 1990, pp:288-297.
Singhal, A. K. “Term Weighting Revisited”, Ph.D. thesis, Cornell University, 1997.
Links
Full Text
http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1374&context=amcis1999
Sonstige Links
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.81.8893
