Abstract
In recent years, Multi-Label Classification (MLC) has become an important task in the field of Supervised Learning. The MLC tasks are omnipresent in real-world problems in which an instance could belong to different classes simultaneously. In this paper, we present a method for MLC using the hidden topic method to enrich data features and using mutual information for feature selection. Our experiments on classifying user reviews about one thousand Vietnamese hotels showed the efficiency of the proposed approach. © Springer-Verlag 2013.
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Pham, T. N., Phan, T. T., Nguyen, P. T., & Ha, Q. T. (2013). Computational Collective Intelligence. Technologies and Applications. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8083(September), 603–611. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-84892909860&partnerID=tZOtx3y1
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