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Published in:
2009 | OriginalPaper | Chapter
Classifying Documents According to Locational Relevance
Authors : Ivo Anastácio, Bruno Martins, Pável Calado
Published in: Progress in Artificial Intelligence
Publisher: Springer Berlin Heidelberg
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This paper presents an approach for categorizing documents according to their implicit locational relevance. We report a thorough evaluation of several classifiers designed for this task, built by using support vector machines with multiple alternatives for feature vectors. Experimental results show that using feature vectors that combine document terms and URL n-grams, with simple features related to the locality of the document (e.g. total count of place references) leads to high accuracy values. The paper also discusses how the proposed categorization approach can be used to help improve tasks such as document retrieval or online contextual advertisement.