Using Collaborative Tagging for Text Classification: From Text Classification to Opinion Mining

• Main Authors: Eric Charton, Marie-Jean Meurs, Ludovic Jean-Louis, Michel Gagnon
• Format: Article
• Language: English
• Published: MDPI AG 2013-11-01
• Series: Informatics
• Subjects: text classification; opinion mining; collaborative corpus; collaborative tagging; machine learning
• Online Access: http://www.mdpi.com/2227-9709/1/1/32

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 D´Efi 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.