Research on Clustering Algorithm Based on Discovery Feature Sub-space Model

被引：0

作者：

Song, Zefeng ^{[1
]}

Yang, Bingru ^{[1
]}

Chen, Zhuo ^{[1
]}

机构：

[1] Univ Sci & Technol Beijing, Sch Informat Engn, Beijing 100083, Peoples R China

来源：

ISISE 2008: INTERNATIONAL SYMPOSIUM ON INFORMATION SCIENCE AND ENGINEERING, VOL 1 | 2008年

关键词：

text clustering; feature extracion; evaluation function;

D O I：

10.1109/ISISE.2008.283

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Based on Discovery Feature Sub-space Model (DFSSM), this paper proposes a new web teat clustring algorithm which characterizes self-stability and powerful antinoise ability. The definitions of cluster and distance measures in the concept space being given. It can distinguishs the most meaningful features from the Concept Space without the evaluation function. The application in the modern long-distance education system prove it is efficient and effective. Through the analysis of results, this algorithm has better performance than traditional approachs.

引用

页码：528 / 532

页数：5

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