Structuring Collections with Scatter/Gather Extensions

Abstract

A major component of sense-making is organizing–grouping, labeling, and summarizing–the data at hand in order to form a useful mental model, a necessary precursor to identifying missing information and to reasoning about the data. Previous work has shown the Scatter/Gather model to be useful in exploratory activities that occur when users encounter unknown document collections. However, the topic structure communicated by Scatter/Gather is closely tied to the behavior of the underlying clustering algorithm; this structure may not reflect the mental model most applicable to the information need. In this paper we describe the initial design of a mixed-initiative information structuring tool that leverages aspects of the well-studied Scatter/Gather model but permits the user to impose their own desired structure when necessary.

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SIGIR
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