A new evolutionary algorithm combining simulated annealing and genetic programming for relevance feedback in fuzzy information retrieval systems
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @Article{cordon:2002:SC,
-
author = "O. Cordon and F. Moya and C. Zarco",
-
title = "A new evolutionary algorithm combining simulated
annealing and genetic programming for relevance
feedback in fuzzy information retrieval systems",
-
journal = "Soft Computing - A Fusion of Foundations,
Methodologies and Applications",
-
year = "2002",
-
volume = "6",
-
number = "5",
-
pages = "308--319",
-
month = aug,
-
keywords = "genetic algorithms, genetic programming, Fuzzy
information retrieval, Relevance feedback, Evolutionary
algorithms, Simulated annealing",
-
ISSN = "1432-7643",
-
DOI = "doi:10.1007/s00500-002-0184-8",
-
abstract = "Relevance feedback techniques have demonstrated to be
a powerful means to improve the results obtained when a
user submits a query to an information retrieval system
as the world wide web search engines. These kinds of
techniques modify the user original query taking into
account the relevance judgements provided by him on the
retrieved documents, making it more similar to those he
judged as relevant. This way, the new generated query
permits to get new relevant documents thus improving
the retrieval process by increasing recall. However,
although powerful relevance feedback techniques have
been developed for the vector space information
retrieval model and some of them have been translated
to the classical Boolean model, there is a lack of
these tools in more advanced and powerful information
retrieval models such as the fuzzy one. In this
contribution we introduce a relevance feedback process
for extended Boolean (fuzzy) information retrieval
systems based on a hybrid evolutionary algorithm
combining simulated annealing and genetic programming
components. The performance of the proposed technique
will be compared with the only previous existing
approach to perform this task, Kraft et al.'s method,
showing how our proposal outperforms the latter in
terms of accuracy and sometimes also in time
consumption. Moreover, it will be showed how the
adaptation of the retrieval threshold by the relevance
feedback mechanism allows the system effectiveness to
be increased.",
- }
Genetic Programming entries for
Oscar Cordon
Felix de Moya
Carmen Zarco Fernandez
Citations