A probabilistic approach to spatiotemporal theme pattern mining on weblogs
Proceedings of the 15th international conference on World Wide Web
Geographical topic discovery and comparison
Proceedings of the 20th international conference on World wide web
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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.