We report here on preliminary work on the use of
evolutionary computing techniques which aims to improve
Boolean information retrieval system performance
through relevance feedback. There are many evolutionary
techniques in computing, such as neural networks and
genetic algorithms. One specific form of genetic
algorithm technique has been used in our study: that of
genetic programming. Terms from relevant documents are
used to randomly create Boolean queries. Boolean
queries are thought of as genetic programming organisms
and, as such, are used for breeding to produce new
organisms. Organisms which perform well, in terms of
how good they are at retrieval, are given a better
chance of being selected for breeding, with the result
being that the overall fitness of the organisms improve
to some extent. The aim is to develop the best Boolean
query for an information need, given a small corpus of
test documents, and then to use that query on the full
collection to retrieve yet more relevant documents.
Martin P. Smith National Institute of Standards and
Technology, Maryland, USA
Martin Smith The University of Huddersfield, UK,
m.smith@hud.ac.uk
c Chartered Institute of Library and Information
Professionals
%0 Journal Article
%1 MartinPSmith:1997:JIS
%A Smith, Martin P.
%A Smith, Martin
%D 1997
%J Journal of Information Science
%K algorithms, genetic programming
%N 6
%P 423--431
%R doi:10.1177/016555159702300603
%T The use of genetic programming to build Boolean
queries for text retrieval through relevance feedback
%V 23
%X We report here on preliminary work on the use of
evolutionary computing techniques which aims to improve
Boolean information retrieval system performance
through relevance feedback. There are many evolutionary
techniques in computing, such as neural networks and
genetic algorithms. One specific form of genetic
algorithm technique has been used in our study: that of
genetic programming. Terms from relevant documents are
used to randomly create Boolean queries. Boolean
queries are thought of as genetic programming organisms
and, as such, are used for breeding to produce new
organisms. Organisms which perform well, in terms of
how good they are at retrieval, are given a better
chance of being selected for breeding, with the result
being that the overall fitness of the organisms improve
to some extent. The aim is to develop the best Boolean
query for an information need, given a small corpus of
test documents, and then to use that query on the full
collection to retrieve yet more relevant documents.
@article{MartinPSmith:1997:JIS,
abstract = {We report here on preliminary work on the use of
evolutionary computing techniques which aims to improve
Boolean information retrieval system performance
through relevance feedback. There are many evolutionary
techniques in computing, such as neural networks and
genetic algorithms. One specific form of genetic
algorithm technique has been used in our study: that of
genetic programming. Terms from relevant documents are
used to randomly create Boolean queries. Boolean
queries are thought of as genetic programming organisms
and, as such, are used for breeding to produce new
organisms. Organisms which perform well, in terms of
how good they are at retrieval, are given a better
chance of being selected for breeding, with the result
being that the overall fitness of the organisms improve
to some extent. The aim is to develop the best Boolean
query for an information need, given a small corpus of
test documents, and then to use that query on the full
collection to retrieve yet more relevant documents.},
added-at = {2008-06-19T17:46:40.000+0200},
author = {Smith, Martin P. and Smith, Martin},
biburl = {https://www.bibsonomy.org/bibtex/2b4202854586fcc76cbad3f9c0481b4f7/brazovayeye},
doi = {doi:10.1177/016555159702300603},
interhash = {54a6474eb080c564ecf62c6c8051178d},
intrahash = {b4202854586fcc76cbad3f9c0481b4f7},
journal = {Journal of Information Science},
keywords = {algorithms, genetic programming},
notes = {Martin P. Smith National Institute of Standards and
Technology, Maryland, USA
Martin Smith The University of Huddersfield, UK,
m.smith@hud.ac.uk
c Chartered Institute of Library and Information
Professionals},
number = 6,
pages = {423--431},
size = {9 pages},
timestamp = {2008-06-19T17:51:51.000+0200},
title = {The use of genetic programming to build Boolean
queries for text retrieval through relevance feedback},
volume = 23,
year = 1997
}