A High Performance Algorithm for Text Feature Automatic Selection

被引：0

作者：

Dai, Jin ^{[1
]}

He, Zhongshi ^{[1
]}

Hu, Feng ^{[2
]}

机构：

[1] Chongqing Univ, Coll Comp Sci, Chongqing 400030, Peoples R China

[2] Chongqing Univ Posts & Telecommun, Inst Comp Sci & Technol, Chongqing 400065, Peoples R China

来源：

ISIP: 2009 INTERNATIONAL SYMPOSIUM ON INFORMATION PROCESSING, PROCEEDINGS | 2009年

关键词：

text classification; feature selection; cloud model; membership degree; dynamic clustering;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Feature selection is an effective method for reducing the size of text feature space. So far, some effective methods for feature selection have been developed. For the purpose of acquiring the optimal number of features, these methods mainly depend on observation or experience. In this paper, by combining the overall with the local distribution of features in categories, a high performance algorithm for feature automation selection (Named FAS) is proposed. By using FAS, the feature set can be obtained automatically. Besides, it can effectively amend the distribution of features by using cloud model theory. Analysis and open experimental results show the selected feature set has fewer features and better classification performance than the existing methods.

引用

页码：414 / +

页数：2

共 50 条

[1] CBFS: High Performance Feature Selection Algorithm Based on Feature Clearness
Seo, Minseok
Oh, Sejong
[J]. PLOS ONE, 2012, 7 (07):
[2] A novel feature selection algorithm for text categorization
Shang, Wenqian
Huang, Houkuan
Zhu, Haibin
Lin, Yongmin
Qu, Youli
Wang, Zhihai
[J]. EXPERT SYSTEMS WITH APPLICATIONS, 2007, 33 (01) : 1 - 5
[3] A Novel Automatic Grouping Algorithm for Feature Selection
Yuan, Qiulong
Fang, Yuchun
[J]. COMPUTER VISION, PT III, 2017, 773 : 592 - 603
[4] Research on Feature Selection Method in Chinese Text Automatic Classification
Hong, Ying
Shao, Xiwen
[J]. PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON APPLIED SCIENCE AND ENGINEERING INNOVATION, 2015, 12 : 1759 - 1763
[5] A feature selection algorithm with redundancy reduction for text classification
Saleh, Sherine Nagi
El-Sonbaty, Yasser
[J]. 2007 22ND INTERNATIONAL SYMPOSIUM ON COMPUTER AND INFORMATION SCIENCES, 2007, : 130 - +
[6] Research on feature selection method in Chinese text automatic classification
Hong, Ying
Geng, Zengmin
[J]. ENERGY SCIENCE AND APPLIED TECHNOLOGY, 2016, : 359 - 361
[7] An Improved Strategy of the Feature Selection Algorithm for the Text Categorization
Yang, Jieming
Lu, Yixin
Liu, Zhiying
[J]. 2019 20TH IEEE/ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCE, NETWORKING AND PARALLEL/DISTRIBUTED COMPUTING (SNPD), 2019, : 3 - 7
[8] A Chaotic Antlion Optimization Algorithm for Text Feature Selection
Chen, Hongwei
Zhou, Xun
Shi, Dewei
[J]. INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2022, 15 (01)
[9] A Chaotic Antlion Optimization Algorithm for Text Feature Selection
Hongwei Chen
Xun Zhou
Dewei Shi
[J]. International Journal of Computational Intelligence Systems, 15
[10] A Text Feature Selection Algorithm Based on Improved TFIDF
Chengcheng Yang
Xingshi He
[J]. PROCEEDINGS OF THE 2008 CHINESE CONFERENCE ON PATTERN RECOGNITION (CCPR 2008), 2008, : 416 - 419

← 1 2 3 4 5 →