Crossover improvement for the genetic algorithm in information retrieval

被引：46

作者：

Vrajitoru, D ^{[1
]}

机构：

[1] Univ Neuchatel, Inst Interfacultaire Informat, CH-2000 Neuchatel, Switzerland

来源：

INFORMATION PROCESSING & MANAGEMENT | 1998年 / 34卷 / 04期

关键词：

D O I：

10.1016/S0306-4573(98)00015-6

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Genetic algorithms (GAs) search for good solutions to a problem by operations inspired from the natural selection of living beings. Among their many uses, we can count information retrieval (IR). In this field, the aim of the GA is to help an IR system to find, in a huge documents text collection, a good reply to a query expressed by the user. The analysis of phenomena seen during the implementation of a GA for IR has brought us to a new crossover operation. This article introduces this new operation and compares it with other learning methods. (C) 1998 Elsevier Science Ltd. All rights reserved.

引用

页码：405 / 415

页数：11

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