Research and Implementation of BHO-Based Content Filtering System

Content filtering technology is a hot research topic in the field of Internet application. The traditional filtering algorithms, such as Error Back Propagation algorithm and KMP algorithm, in which sensitive words will be matched with the content to be retrieved one by one, and this reduces the efficiency when massive data is filtered. To solve the shortcoming above, a prototype of content filtering system based on BHO (Browser Helper Object) is proposed in this paper. The system includes URL filtering and content filtering. It stores sensitive words by way of Hash function to improve the retrieval speed, and matches them by using Longest Prefix Match algorithm and Binary Search algorithm. At last, the system is tested in two ways (accuracy and filtering time) and performs well.