Selection of Information Sources Using a Genetic Algorithm

被引：5

作者：

Lebib, Fatma Zohra ^{[1
,2
]}

Drias, Habiba ^{[1
]}

Mellah, Hakima ^{[2
]}

机构：

[1] LRIA, USTHB, Algiers, Algeria

[2] CERIST, Algiers, Algeria

来源：

RECENT ADVANCES IN INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 1 | 2017年 / 569卷

关键词：

Information sources selection; Distributed information retrieval; Bio-inspired methods; Genetic algorithms; RETRIEVAL;

D O I：

10.1007/978-3-319-56535-4_6

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We address the problem of information sources selection in a context of a large number of distributed sources. We formulate the sources selection problem as a combinatorial optimization problem in order to yield the best set of relevant information sources for a given query. We define a solution as a combination of sources among a huge pre-defined set of sources. We propose a genetic algorithm to tackle the issue by maximizing the similarity between a selection and the query. Extensive experiments were performed on databases of scientific research documents covering different domains such as computer science and medicine. The results based on the precision measure are very encouraging.

引用

页码：60 / 70

页数：11

共 29 条

[1]

Al Mashagba E., 2011, INT J COMP SCI, V8, P450

[2]

Araujo L, 2010, IEEE C EV COMP, P1

[3] Structure of morphologically expanded queries: A genetic algorithm approach [J].