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We describe our system for finding good answers in a community forum, asdefined in SemEval-2016, Task 3 on Community Question Answering. Our approachrelies on several semantic similarity features based on fine-tuned wordembeddings and topics similarities. In the main Subtask C, our primarysubmission was ranked third, with a MAP of 51.68 and accuracy of 69.94. InSubtask A, our primary submission was also third, with MAP of 77.58 andaccuracy of 73.39.

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