Applying layered multi-population genetic programming on learning to rank for information retrieval
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{Lin:2012:ICMLC,
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author = "Jung Yi Lin and Jen-Yuan Yeh and Chao-Chung Liu",
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booktitle = "International Conference on Machine Learning and
Cybernetics (ICMLC 2012)",
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title = "Applying layered multi-population genetic programming
on learning to rank for information retrieval",
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year = "2012",
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volume = "5",
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pages = "1754--1759",
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size = "6 pages",
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abstract = "Information retrieval (IR) returns a relative ranking
of documents with respect to a user query. Learning to
rank for information retrieval (LR4IR) employs
supervised learning techniques to address this problem,
and it aims to produce a ranking model automatically
for defining a proper sequential order of related
documents based on the query. The ranking model
determines the relationship degree between documents
and the query. In this paper an improved version of
RankGP is proposed. It uses layered multi-population
genetic programming to obtain a ranking function which
consists of a set of IR evidences and particular
predefined operators. The proposed method is capable to
generate complex functions through evolving small
populations. In this paper, LETOR 4.0 was used to
evaluate the effectiveness of the proposed method and
the results showed that the method is competitive with
other LR4IR Algorithms.",
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keywords = "genetic algorithms, genetic programming, document
handling, learning (artificial intelligence), query
processing, LETOR 4.0, LR4IR, RankGP, document ranking,
layered multipopulation genetic programming, learning
to rank for information retrieval, ranking function,
supervised learning techniques, user query, Abstracts,
Programming, Sociology, Statistics, Evolutionary
computation, Learning to rank for Information
Retrieval, Ranking function",
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DOI = "doi:10.1109/ICMLC.2012.6359640",
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ISSN = "2160-133X",
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notes = "Also known as \cite{6359640}",
- }
Genetic Programming entries for
Mick Jung-Yi Lin
Jen-Yuan Yeh
Chao Chung Liu
Citations