We describe our system for finding good answers in a community forum, as defined in SemEval-2016, Task 3 on Community Question Answering. Our approach relies on several semantic similarity features based on fine-tuned word embeddings and topics similarities. In the main Subtask C, our primary submission was ranked third, with a MAP of 51.68 and accuracy of 69.94. In Subtask A, our primary submission was also third, with MAP of 77.58 and accuracy of 73.39.
CITATION STYLE
Mihaylov, T., & Nakov, P. (2016). SemanticZ at SemEval-2016 task 3: Ranking relevant answers in community Question Answering using semantic similarity based on fine-tuned word embeddings. In SemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings (pp. 879–886). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s16-1136
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