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» Ranking Function Discovery by Genetic Programming for Robust...
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114
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TREC
2003
15 years 1 months ago
Ranking Function Discovery by Genetic Programming for Robust Retrieval
Ranking functions are instrumental for the success of an information retrieval (search engine) system. However nearly all existing ranking functions are manually designed based on...
Li Wang, Weiguo Fan, Rui Yang, Wensi Xi, Ming Luo,...
105
Voted
TREC
2004
15 years 1 months ago
Can We Get A Better Retrieval Function From Machine?
The quality of an information retrieval system heavily depends on its retrieval function, which returns a similarity measurement between the query and each document in the collect...
Weiguo Fan, Wensi Xi, Edward A. Fox, Li Wang
123
Voted
CLEF
2006
Springer
15 years 4 months ago
The University of New South Wales at GeoCLEF 2006
This paper describes our participation in the GeoCLEF monolingual English task of the Cross Language Evaluation Forum 2006. The main objective of this study is to evaluate the retr...
You-Heng Hu, Linlin Ge
131
Voted
CEC
2011
IEEE
14 years 11 days ago
Cost-benefit analysis of using heuristics in ACGP
—Constrained Genetic Programming (CGP) is a method of searching the Genetic Programming search space non-uniformly, giving preferences to certain subspaces according to some heur...
John W. Aleshunas, Cezary Z. Janikow
ECAI
2010
Springer
15 years 1 months ago
Learning Aggregation Functions for Expert Search
Abstract. Machine learning techniques are increasingly being applied to problems in the domain of information retrieval and text mining. In this paper we present an application of ...
Ronan Cummins, Mounia Lalmas, Colm O'Riordan