Using Collaborative Tagging for Text Classification: From Text Classification to Opinion Mining
Journal Title: Informatics - Year 2014, Vol 1, Issue 1
Abstract
Numerous initiatives have allowed users to share knowledge or opinions using collaborative platforms. In most cases, the users provide a textual description of their knowledge, following very limited or no constraints. Here, we tackle the classification of documents written in such an environment. As a use case, our study is made in the context of text mining evaluation campaign material, related to the classification of cooking recipes tagged by users from a collaborative website. This context makes some of the corpus specificities difficult to model for machine-learning-based systems and keyword or lexical-based systems. In particular, different authors might have different opinions on how to classify a given document. The systems presented hereafter were submitted to the DEfi ´ Fouille de Textes 2013 evaluation campaign, where they obtained the best overall results, ranking first on task 1 and second on task 2. In this paper, we explain our approach for building relevant and effective systems dealing with such a corpus.
Authors and Affiliations
Eric Charton, Marie-Jean Meurs, Ludovic Jean-Louis and Michel Gagnon
Keywords
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- EP ID EP44035
- DOI https://doi.org/10.3390/informatics1010032
- Views 308
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