Mining interesting topics for Web information gathering and Web personalization

Abstract

The quality of discovery patterns is crucial for building satisfactory systems of Web text mining. It is no doubt that we can find numerous frequent patterns from Web documents. However, there are many meaningless frequent patterns. This paper presents a novel method to improve the quality of discovered patterns. It generalizes discovered patterns into interesting topics in order to acquire the necessary useful information. The experimental results also verify the proposed method is promising.