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A Sensemaking-based Information Foraging and Summarization System in Business Environments

Nowadays, the amount of information all around the Web and within an enterprise can be overwhelming. In business environments information workers need a system that can actively help them make the most effective decision. This paper proposes a sensemaking-based information summarization system, called Topic Tracker, which can automatically find, gather and analyze relevant information based on context in depth so as to better understand data to support efficient decision making. The architecture of Topic Tracker includes three major components – topic detection, knowledge discovery, and information management, and four data management processes – search, analysis, summarization and retrieval. To demonstrate our thought an implementation result is presented and some future works are discussed at the end.