UH-PRHLT at SemEval-2016 task 3: Combining lexical and semantic-based features for community question answering

Abstract

In this work we describe the system built for the three English subtasks of the Se-mEval 2016 Task 3 by the Department of Computer Science of the University of Houston (UH) and the Pattern Recognition and Human Language Technology (PRHLT) research center - Universitat Politecnica de Valencia: UH-PRHLT. Our system represents instances by using both lexical and semantic-based similarity measures between text pairs. Our semantic features include the use of distributed representations of words, knowledge graphs generated with the BabelNet multilingual semantic network, and the FrameNet lexical database. Experimental results outperform the random and Google search engine baselines in the three English sub-tasks. Our approach obtained the highest results of subtask B compared to the other task participants.