Genetic-based approaches in ranking function discovery and optimization in information retrieval -- A framework

Created by W.Langdon from gp-bibliography.bib Revision:1.8110

@Article{Fan2009398,

• author = "Weiguo Fan and Praveen Pathak and Mi Zhou",
• title = "Genetic-based approaches in ranking function discovery and optimization in information retrieval -- A framework",
• journal = "Decision Support Systems",
• volume = "47",
• number = "4",
• pages = "398--407",
• year = "2009",
• note = "Smart Business Networks: Concepts and Empirical Evidence",
• ISSN = "0167-9236",
• DOI = "doi:10.1016/j.dss.2009.04.005",
• URL = "http://www.sciencedirect.com/science/article/B6V8S-4W2W5G2-2/2/891e4aeaad9141e2bfe99d4477f96c1a",
• keywords = "genetic algorithms, genetic programming, Information retrieval, Artificial intelligence, Evolutionary computations, Data fusion",
• abstract = "An Information Retrieval (IR) system consists of document collection, queries issued by users, and the matching/ranking functions used to rank documents in the predicted order of relevance for a given query. A variety of ranking functions have been used in the literature. But studies show that these functions do not perform consistently well across different contexts. In this paper we propose a two-stage integrated framework for discovering and optimising ranking functions used in IR. The first stage, discovery process, is accomplished by intelligently leveraging the structural and statistical information available in HTML documents by using Genetic Programming techniques to yield novel ranking functions. In the second stage, the optimization process, document retrieval scores of various well-known ranking functions are combined using Genetic Algorithms. The overall discovery and optimization framework is tested on the well-known TREC collection of web documents for both the ad-hoc retrieval task and the routing task. Using our framework we observe a significant increase in retrieval performance compared to some of the well-known stand alone ranking functions.",

}

Genetic Programming entries for Weiguo Fan Praveen Pathak Mi Zhou

Citations