Chapter

Progress in Artificial Intelligence

Volume 5816 of the series Lecture Notes in Computer Science pp 598-609

Classifying Documents According to Locational Relevance

  • Ivo AnastácioAffiliated withINESC-ID, Instituto Superior Técnico
  • , Bruno MartinsAffiliated withINESC-ID, Instituto Superior Técnico
  • , Pável CaladoAffiliated withINESC-ID, Instituto Superior Técnico

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Abstract

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.

Keywords

Document Classification Geographic Text Mining