Ensemble Approaches for Large-Scale Multi-Label Classification and Question Answering in Biomedicine

Y. Papanikolaou, D. Dimitriadis, G. Tsoumakas, M. Laliotis, N. Markantonatos, I. Vlahavas, “Ensemble Approaches for Large-Scale Multi-Label Classification and Question Answering in Biomedicine”, Proceedings BioASQ 2014 Workshop, Sheffield, UK, 2014.

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Author(s): Y. Papanikolaou, D. Dimitriadis, Grigorios Tsoumakas, M. Laliotis, N. Markantonatos, I. Vlahavas

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Appeared In: Proceedings BioASQ 2014 Workshop, Sheffield, UK, 2014.

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2014, Dimitriadis, Laliotis, Markantonatos, Papanikolaou, Tsoumakas, Vlahavas

Abstract: This paper documents the systems that we developed for our participation in the BioASQ 2014 large-scale bio-medical semantic indexing and question answering challenge. For the large-scale semantic indexing task, we employed a novel multi-label ensemble method consisting of support vector machines, labeled Latent Dirichlet Allocation models and meta-models predicting the number of relevant labels. This method proved successful in our experiments as well as during the competition. For the question answering task we combined different techniques for scoring of candidate answers based on recent literature.