Discovery of video websites based on machine learning
Chengqi Zhang, Wenqian Shang · 2012
The supervision of video websites has become extremely important with the rapid development of web, The first problem to overcome is automatically detecting of video websites. For the traditional limitations of artificial discrimination, this paper presents a video website discovery method based on machine learning. First we adopt a crawler to crawl video page description information, then we preprocess these text information. After these steps, we adopt a Naïve Bayes classifier to classify this text information. In addition, through the combination of sensitive words matching, we can realize the supervision of sensitive information.