Acquiring Organized Information from News by Incremental Theme Refinements

Abstract

We propose an interactive system which allows a user to efficiently acquire organized information from a news corpus. Initiated by a topic specified by a user, the system first extracts a relevant set of sentences, from the corpus and divides them into themes each designated by an additional query term. The user then can select one of them, and the system maintains an interactive information access session by incrementally refining the search queries. This incremental process enables user's topic-specific yet efficient information access activities. Small-scaled experiments confirmed that the proposed system could provide the user with more effective supports than an ordinary search engine in the sense that it concisely provides a set of chronologically-sorted sentences classified by the themes. The experiments however further identified important issues, including the reduction of duplicate themes and sentences, and the deletion of sentences that cannot tell their meaning without neighboring contexts. For future work, we first implement automatic title generation, and then complete a total system.