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Latent Contextual Indexing of Annotated Documents (2012)
BibTeX
@MISC{Sengstock12latentcontextual,
author = {Christian Sengstock and Michael Gertz},
title = {Latent Contextual Indexing of Annotated Documents},
year = {2012}
}
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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.
Keyphrases
latent contextual indexing contextual topic annotated document context-feature space index context-annotated document document collection document feature flexible framework context domain particular meaning case study geographic phenomenon georeferenced wikipedia article repetitive event document clustering dimensionality reduction contextual knowledge
