On the base of researching currently popular text topic extraction technologies, a new text topic automatic abstracting method is proposed based on rough set theory and rough similarity. Firstly it separated a text into words and sentences to complete information segmentation, and then constructed a similarity matrix by computing the rough similarity between different words to realize the text clustering, finally extracted representative sentences from each class to generate the text topic. The experiment shows that the method is feasible and effective.
Research Concerning Topic Extraction Method Using Burst Levels in Microblogs
