- author = "Weiguo Fan and Michael D. Gordon and Praveen Pathak",
- title = "Automatic generation of matching functions by genetic programming for effective information retrieval",
- booktitle = "Proceedings of the 1999 Americas Conference on Information Systems",
- year = "1999",
- editor = "W. David Haseman and Derek L. Nazareth",
- pages = "49--51",
- address = "Milwaukee, WI, USA",
- month = "13-15 " # aug,
- organisation = "Association for Information Systems",
- keywords = "genetic algorithms, genetic programming",
-
URL = "
http://filebox.vt.edu/users/wfan/paper/Amcis_final.pdf",
- size = "3 pages",
- 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.",
-
notes = "AMCIS99
https://commerce.mindspring.com/www.icisnet.org/proc.html
Prototype implemented in C. Fitness based on user feedback
Duplicate entry \cite{Fan:1999:AMCIS} removed 21 Oct 2006",
