Implementation of unsupervised and supervised learning systems for multilingual text categorization

被引：0
|
作者：
Lee, Chung-Hong [1 ]
Yang, Hsin-Chang [2 ]
机构：
[1] Natl Kaohsiung Univ Appl Sci, Dept Elect Engn, Kaohsiung, Taiwan
[2] Natl Univ Kaohsiung, Dept Informat Management, Kaohsiung, Taiwan
来源：
INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY, PROCEEDINGS | 2007年
关键词：
D O I：
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中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper we discuss the implementation of the leading supervised and unsupervised approaches for multilingual text categorization. We selected Support Vector Machines (SVV) and Latent Semantic Indexing (LSI) techniques as representatives of supervised and unsupervised methods for system implementation, respectively The preliminary results show that our platform models including both supervised and unsupervised learning methods have the potentials for multilingual text categorization.
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页码：377 / +
页数：2
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