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| Content Provider | ACM Digital Library |
|---|---|
| Author | Gertz, Michael Sengstock, Christian |
| Abstract | In this paper we propose a simple and flexible framework to index context-annotated documents, e.g., documents with timestamps or georeferences, by contextual topics. A contextual topic is a distribution over document features with a particular meaning in the context domain, such as a repetitive event or a geographic phenomenon. Such a framework supports document clustering, labeling, and search, with respect to contextual knowledge contained in the document collection. To realize the framework, we introduce an approach to project documents into a context-feature space. Then, dimensionality reduction is used to extract contextual topics in this context-feature space. The topics can then be projected back onto the documents. We demonstrate the utility of our approach with a case study on georeferenced Wikipedia articles. |
| Starting Page | 593 |
| Ending Page | 594 |
| Page Count | 2 |
| File Format | |
| ISBN | 9781450312301 |
| DOI | 10.1145/2187980.2188143 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2012-04-16 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Georeferenced data Exploratory data analysis Topic models Document context Latent semantic analysis |
| Content Type | Text |
| Resource Type | Article |
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