A new evolutionary algorithm combining simulated annealing and genetic programming for relevance feedback in fuzzy information retrieval systems
type: Item
instance of: scholarly article
title: A new evolutionary algorithm combining simulated annealing and genetic programming for relevance feedback in fuzzy information retrieval systems
zbMATH Open document ID: 1027.68548
author: F. Moya
author: C. Zarco
author: Oscar Cordón
published in: Soft Computing
publication date: 2003-03-18T00:00:00Z
review text: 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.
Mathematics Subject Classification ID: 68P20
Mathematics Subject Classification ID: 68U99
Mathematics Subject Classification ID: 68T20
zbMATH DE Number: 1883968
zbMATH Keywords: relevance feedback
MaRDI profile type: Publication
full work available at URL: s00500-002-0184-8
OpenAlex ID: W2165152343
DOI: 10.1007/S00500-002-0184-8
description: scientific article; zbMATH DE number 1883968