Genetic algorithms in relevance feedback: a second test and new contributions

The present work is the continuation of an earlier study which reviewed the literature on relevance feedback genetic techniques that follow the vector space model (the model that is most commonly used in this type of application), and implemented them so that they could be compared with each other a...

Full description

Saved in:
Bibliographic Details
Published in:Information processing & management 2003-09, Vol.39 (5), p.669-687
Main Authors: López-Pujalte, Cristina, Guerrero-Bote, Vicente P., de Moya-Anegón, Félix
Format: Article
Language:English
Subjects:
Algorithms
Automatic indexing
Automatic text analysis
Exact sciences and technology
Genetic algorithms
Indexing
Information and communication sciences
Information processing and retrieval
Information retrieval
Information retrieval. Man machine relationship
Information science. Documentation
Relevance feedback
Research process. Evaluation
Sciences and techniques of general use
Studies
Test collections
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The present work is the continuation of an earlier study which reviewed the literature on relevance feedback genetic techniques that follow the vector space model (the model that is most commonly used in this type of application), and implemented them so that they could be compared with each other as well as with one of the best traditional methods of relevance feedback––the Ide dec-hi method. We here carry out the comparisons on more test collections (Cranfield, CISI, Medline, and NPL), using the residual collection method for their evaluation as is recommended in this type of technique. We also add some fitness functions of our own design.
ISSN:0306-4573
1873-5371
DOI:10.1016/S0306-4573(02)00044-4