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SCIR-QA at SemEval-2017 Task 3: CNN Model Based on Similar and Dissimilar Information between Keywords for Question Similarity

机译:SCIR-QA在SemEval-2017上的任务3:问题相似度基于关键词之间相似和不同信息的CNN模型

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We describe a method of calculating the similarity between questions in community QA. Questions in cQA are usually very long and there are a lot of useless information about calculating the similarity between questions. Therefore, we implement a CNN model based on similar and dissimilar information on questions keywords. We extract the keywords of questions, and then model the similar and dissimilar information between the keyword-s, and use the CNN model to calculate the similarity.
机译:我们描述了一种计算社区质量检查中问题之间相似度的方法。 cQA中的问题通常很长,关于计算问题之间的相似度有很多无用的信息。因此,我们基于问题关键字的相似和不相似信息来实现CNN模型。我们提取问题的关键字,然后对关键字s之间的相似和不相似信息建模,然后使用CNN模型计算相似度。

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