Discovery of context-specific ranking functions for effective information retrieval using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@Article{Fan2003a,

• author = "Weiguo Fan and Michael D. Gordon and Praveen Pathak",
• title = "Discovery of context-specific ranking functions for effective information retrieval using genetic programming",
• journal = "IEEE Transactions on Knowledge and Data Engineering",
• year = "2004",
• volume = "16",
• number = "4",
• pages = "523--527",
• month = apr,
• keywords = "genetic algorithms, genetic programming, data mining, information retrieval, search engines, tree data structures, Internet, TREC data, context-specific ranking function discovery, corporate intranets, fixed ranking strategy, information routing, intelligent contextual information retrieval, search engines, term weighting strategy, text mining",
• ISSN = "1041-4347",
• DOI = "doi:10.1109/TKDE.2004.1269663",
• size = "5 pages",
• 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. 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.",
• notes = "http://filebox.vt.edu/users/wfan/pub_area.html",

}

Genetic Programming entries for Weiguo Fan Michael D Gordon Praveen Pathak

Citations