Applying Genetic Algorithm In Query Improvement Problem
Data(s) |
09/04/2009
03/09/2009
09/04/2009
03/09/2009
2007
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Resumo |
This paper presents an adaptive method using genetic algorithm to modify user’s queries, based on relevance judgments. This algorithm was adapted for the three well-known documents collections (CISI, NLP and CACM). The method is shown to be applicable to large text collections, where more relevant documents are presented to users in the genetic modification. The algorithm shows the effects of applying GA to improve the effectiveness of queries in IR systems. Further studies are planned to adjust the system parameters to improve its effectiveness. The goal is to retrieve most relevant documents with less number of non-relevant documents with respect to user's query in information retrieval system using genetic algorithm. |
Identificador |
1313-048X |
Idioma(s) |
en |
Publicador |
Institute of Information Theories and Applications FOI ITHEA |
Palavras-Chave | #Genetic Algorithm |
Tipo |
Article |