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| Content Provider | ACM Digital Library |
|---|---|
| Author | Talbot, Justin Alonso, Omar |
| 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. |
| Starting Page | 697 |
| Ending Page | 698 |
| Page Count | 2 |
| File Format | |
| ISBN | 9781605581644 |
| DOI | 10.1145/1390334.1390457 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2008-07-20 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Sense-making Text summarization Scatter/gather Clustering |
| Content Type | Text |
| Resource Type | Article |
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