Journal article
Discovery of context-specific ranking functions for effective information retrieval using genetic programming
IEEE transactions on knowledge and data engineering, Vol.16(4), pp.523-527
04/01/2004
DOI: 10.1109/TKDE.2004.1269663
Abstract
The Internet and corporate Intranets have brought a lot of information. People usually resort to search engines to find required information. However, these systems tend to use only one fixed ranking strategy regardless of the contexts. This poses serious performance problems when characteristics of different users, queries, and text collections are taken into account. In this paper, we argue that the ranking strategy should be context specific and we propose a new systematic method that can automatically generate ranking strategies for different contexts based on Genetic Programming (GP). The new method was tested on TREC data and the results are very promising.
Details
- Title: Subtitle
- Discovery of context-specific ranking functions for effective information retrieval using genetic programming
- Creators
- W G Fan - Virginia TechM D GordonP Pathak - University of Florida
- Resource Type
- Journal article
- Publication Details
- IEEE transactions on knowledge and data engineering, Vol.16(4), pp.523-527
- Publisher
- IEEE
- DOI
- 10.1109/TKDE.2004.1269663
- ISSN
- 1041-4347
- eISSN
- 1558-2191
- Number of pages
- 5
- Language
- English
- Date published
- 04/01/2004
- Academic Unit
- Business Analytics
- Record Identifier
- 9984380419202771
Metrics
1 Record Views