摘要
With the explosive growth of Internet information, it is more and more important to fetch real-time and related information. And it puts forward higher requirement on the speed of webpage classification which is one of common methods to retrieve and manage information. To get a more efficient classifier, this paper proposes a webpage classification method based on locality sensitive hash function. In which, three innovative modules including building feature dictionary, mapping feature vectors to fingerprints using Localitysensitive hashing, and extending webpage features are contained. The compare results show that the proposed algorithm has better performance in lower time than the naive bayes one.
出处
《国际计算机前沿大会会议论文集》
2015年第1期73-75,共3页
International Conference of Pioneering Computer Scientists, Engineers and Educators（ICPCSEE）
