摘要
We applied the decision tree algorithm to learn association rules between webpage’s category(pornographic or normal) and the critical features.Based on these rules, we proposed an efficient method of filtering pornographic webpages with the following major advantages: 1) a weighted window-based technique was proposed to estimate for the condition of concept drift for the keywords found recently in pornographic webpages; 2) checking only contexts of webpages without scanning pictures; 3) an incremental learning mechanism was designed to incrementally update the pornographic keyword database.
We applied the decision tree algorithm to learn association rules between webpage's category(pornographic or normal) and the critical features.Based on these rules, we proposed an efficient method of filtering pornographic webpages with the following major advantages: 1) a weighted window-based technique was proposed to estimate for the condition of concept drift for the keywords found recently in pornographic webpages; 2) checking only contexts of webpages without scanning pictures; 3) an incremental learning mechanism was designed to incrementally update the pornographic keyword database.
基金
supported by MOST under Grant No.MOST 103-2410-H-004-112
作者简介
Jyh-Jian Sheu is currently an associate professor with the College of Communication, National Chengchi University, Taipei. He received his B.B.A.degree in management information systemsfrom National Chengchi University, andhis M.S. and Ph.D. degrees in computerand information science from NationalChiao Tung University, Hsinchu.e-mail: jjsheu@nccu.edu.tw
