Application of support vector machine in junk information filtering

被引:0
|
作者
Network and Information Center, Qiqihar University, No. 42, Wenhua Street, Qiqihar, China [1 ]
机构
来源
ICIC Express Lett. | / 5卷 / 1367-1371期
关键词
Bayesian classifier - Comparison result - Evaluation index - Evaluation system - Junk information - Support vector machine algorithm - SVM - Text classification;
D O I
暂无
中图分类号
学科分类号
摘要
We propose a filtering method junk information filtering based on support vector machine (SVM) algorithm. By means of performance evaluation indexes universally applied in such fields as text classification and information retrieval, an evaluation system for filtering junk messages is established. The proper kernel function and its parameters are selected to construct a classifier of SVM. The classifier of SVM and the traditional Bayesian classifier is tested and evaluated through stimulation experiments and evaluation system. The comparison results show that the classifier of SVM improves the accuracy of filtering messages, and verifies the effectiveness of the algorithm of SVM. © ICIC International
引用
收藏
相关论文
共 50 条
  • [1] Support Vector Machine Filtering for MEMS gyroscope
    Peng, Yang
    Qing, Li
    [J]. PROCEEDINGS OF THE THIRD INTERNATIONAL SYMPOSIUM ON TEST AUTOMATION & INSTRUMENTATION, VOLS 1 - 4, 2010, : 304 - 308
  • [2] Image filtering using support vector machine
    Liu, Huaping
    Sun, Fuchun
    Sun, Zengqi
    [J]. ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 2, PROCEEDINGS, 2006, 3972 : 533 - 538
  • [3] Identifying junk electronic mail in Microsoft Outlook with a support vector machine
    Woitaszek, M
    Shaaban, M
    Czernikowski, R
    [J]. 2003 SYMPOSIUM ON APPLICATIONS AND THE INTERNET, PROCEEDINGS, 2003, : 166 - 169
  • [4] Effective Information Filtering Mining of Internet of Brain Things Based on Support Vector Machine
    Zhao, Xiaofeng
    Zang, Weihua
    Lv, Rulan
    Cui, Wei
    [J]. IEEE ACCESS, 2019, 7 : 191 - 202
  • [5] Application of support vector machine based on information spectrum entropy in machine state identification
    Pan, Ming-Qing
    Zhou, Xiao-Jun
    Yang, Chen-Long
    Pang, Mao
    [J]. Chinese Journal of Sensors and Actuators, 2005, 18 (02) : 277 - 280
  • [6] A Biased Support Vector Machine approach to web filtering
    Du, AN
    Fang, BX
    Li, B
    [J]. PATTERN RECOGNITION AND DATA MINING, PT 1, PROCEEDINGS, 2005, 3686 : 363 - 370
  • [7] The Application of Support Vector Regression in Particle Filtering
    Qiang, Xingzi
    Xue, Rui
    Zhu, Yanbo
    [J]. 2021 IEEE INTERNATIONAL CONFERENCE ON INFORMATION COMMUNICATION AND SOFTWARE ENGINEERING (ICICSE 2021), 2021, : 5 - 9
  • [8] Study on signal filtering based on support vector machine
    School of Electronics and Information Technology, Harbin Institute of Technology, Harbin 150001, China
    [J]. Hsi An Chiao Tung Ta Hsueh, 2006, 4 (427-431):
  • [9] A support vector machine application on vehicles
    Del Rose, M
    Reed, J
    [J]. APPLICATIONS AND SCIENCE OF NEURAL NETWORKS, FUZZY SYSTEMS, AND EVOLUTIONARY COMPUTATION IV, 2001, 4479 : 144 - 149
  • [10] Study of support vector machine based adaptive Kalman filtering
    College of Automation, Northwestern Polytechnical University, Xi'an 710072, China
    不详
    不详
    [J]. Kongzhi yu Juece Control Decis, 2008, 8 (949-952): : 949 - 952