Document Management with Ant Colony Optimization Metaheuristic: A Fuzzy Text Clustering Approach Using Pheromone Trails

被引：0
|
作者：
Cobo, Angel [1 ]
Rocha, Rocio [2 ]
机构：
[1] Univ Cantabria, Dept Appl Math & Computat Sci, Avda Los Castros S-N, E-39005 Santander, Spain
[2] Univ Cantabria, Dept Business Adm, Avda Los Castros S-N, E-39005 Santander, Spain
来源：
SOFT COMPUTING IN INDUSTRIAL APPLICATIONS | 2011年 / 96卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper proposes an ant colony optimization (ACO) algorithm to deal with fuzzy document clustering problems. A specialized glossary and a thesaurus are used in order to extract features of the documents and to obtain a language-independent vector representation that can be used to measure similarities between documents written in different languages. The pheromone trails obtained in the ACO process are used to determine membership values in a fuzzy clustering. To illustrate the behavior of the algorithm, it was applied to a corpus of bilingual documents in different areas of economic and management.
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页码：261 / +
页数：2
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