Subtopic mining based on three-level hierarchical search intentions

Abstract

This paper proposes a subtopic mining method based on three-level hierarchical search intentions. Various subtopic candidates are extracted from web documents using a simple pattern, and higherlevel and lower-level subtopics are selected from these candidates. The selected subtopics as second-level subtopics are ranked by a proposed measure, and are expanded and re-ranked considering the characteristics of resources. Using general terms in the higher-level subtopics, we make second-level subtopic groups and generate first-level subtopics. Our method achieved better performance than a state of the art method.