SemanticZ at SemEval-2016 Task 3: Ranking Relevant Answers in Community Question Answering Using Semantic Similarity Based on Fine-tuned Word Embeddings

November 20, 2019 ยท Declared Dead ยท ๐Ÿ› International Workshop on Semantic Evaluation

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Authors Todor Mihaylov, Preslav Nakov arXiv ID 1911.08743 Category cs.CL: Computation & Language Cross-listed cs.AI, cs.IR Citations 59 Venue International Workshop on Semantic Evaluation Last Checked 4 months ago
Abstract
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.
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