Text Data Mining with Optimized Pattern Discovery

This paper describes an application of the optimized pattern discovery framework to text and Web mining. In particular, we introduce a class of simple combinatorial patterns over phrases, called proximity phrase association patterns, and consider the problem of nding the patterns that optimizes a given statistical measure in a large collection of unstructured texts. For this class of patterns, we develop fast and robust text mining algorithms based on techniques from computational geometry and string matching. Then, we made experiments on large collections of documents and on Web pages to evaluate the proposed method.