Improvement of Text Feature Selection Method based on TFIDF

被引：17
|
作者：
Qu, Shouning [1 ]
Wang, Sujuan [1 ]
Zou, Yan [1 ]
机构：
[1] Univ Jinan, Sch Informat Sci & Engn, Jinan 250022, Shandong, Peoples R China
来源：
2008 INTERNATIONAL SEMINAR ON FUTURE INFORMATION TECHNOLOGY AND MANAGEMENT ENGINEERING, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/FITME.2008.25
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
TFIDF is a kind of common methods used to select the text feature, but it has many disadvantages. First, the method undervalues that this term can represent the characteristic of the documents of this class if it only frequently appears in the documents belongs to the same class while infrequently in the documents of the other class. Second TFIDF neglects the relations between the feature and the class. The paper proposed the improved TFIDF strategy, and combined with the text classification method of simple distance vector to compare to traditional TFIDF, and obtained the very good classified effect, the experiment proved its feasibility.
引用
收藏
页码：79 / 81
页数：3
相关论文
共 50 条
  • [41] A new unsupervised feature selection method for text clustering based on genetic algorithms
    Shamsinejadbabki, Pirooz
    Saraee, Mohammad
    JOURNAL OF INTELLIGENT INFORMATION SYSTEMS, 2012, 38 (03) : 669 - 684
  • [42] Feature selection based on feature interactions with application to text categorization
    Tang, Xiaochuan
    Dai, Yuanshun
    Xiang, Yanping
    EXPERT SYSTEMS WITH APPLICATIONS, 2019, 120 : 207 - 216
  • [43] Text Categorization Based on Clustering Feature Selection
    Zhou, Xiaofei
    Hu, Yue
    Guo, Li
    2ND INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT, ITQM 2014, 2014, 31 : 398 - 405
  • [44] Rank Aggregation based Text Feature Selection
    Wu, Ou
    Zuo, Haiqiang
    Zhu, Mingliang
    Hu, Weiming
    Gao, Jun
    Wang, Hanzi
    2009 IEEE/WIC/ACM INTERNATIONAL JOINT CONFERENCES ON WEB INTELLIGENCE (WI) AND INTELLIGENT AGENT TECHNOLOGIES (IAT), VOL 1, 2009, : 165 - +
  • [45] Text Feature Selection Based on Class Subspace
    Zhou, Xiaofei
    Guo, Li
    Wang, Tianyi
    Hu, Yue
    2014 IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOP (ICDMW), 2014, : 267 - 273
  • [46] Text classification framework for short text based on TFIDF-FastText
    Chawla, Shrutika
    Kaur, Ravreet
    Aggarwal, Preeti
    MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (26) : 40167 - 40180
  • [47] An Improved Text Feature Selection Method for Transfer Learning
    Liu, Jiang
    Wang, Hao
    Liu, Jun
    CONTEMPORARY RESEARCH ON E-BUSINESS TECHNOLOGY AND STRATEGY, 2012, 332 : 600 - +
  • [48] An improved text feature selection method for transfer learning
    Liu, Jiang
    Wang, Hao
    Liu, Jun
    Communications in Computer and Information Science, 2013, 332 : 600 - 611
  • [49] A parallel feature selection method study for text classification
    Li, Zhao
    Lu, Wei
    Sun, Zhanquan
    Xing, Weiwei
    NEURAL COMPUTING & APPLICATIONS, 2017, 28 : S513 - S524
  • [50] Statera: A Balanced Feature Selection Method for Text Classification
    Gama Bispo, Braian Varjao
    Rios, Tatiane Nogueira
    2018 7TH BRAZILIAN CONFERENCE ON INTELLIGENT SYSTEMS (BRACIS), 2018, : 260 - 265
12345