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A New Approach for Finding and Ranking Question – Answering Pairs in Community Question Answering

机译:查找和排序问题的新方法-社区问答中的答案对

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Objective: To help users receive immediate answers when they submit an input question to the community Question Answering (cQA) websites. Methods: To find and ranking question - answering pairs in cQA related to the input question, in this paper we investigate various aspects of understanding questions as well as answers to extract different features kinds from them. Then all these obtained features are combined into a machine learning based framework for getting similarity existing question - answering pairs as well as for ranking these pairs. Finding: Besides the traditional features such as bag of n-grams we will use more efficient aspects that include word embeddings, question categories and.
机译:目标:帮助用户在向社区问答网站(cQA)网站提交输入问题时立即获得答案。方法:在cQA中查找和排序与输入问题相关的问答对,在本文中,我们研究了理解问题的各个方面以及从中提取不同特征种类的答案。然后,将所有这些获得的特征组合到基于机器学习的框架中,以获取现有问题的相似性-回答对以及对这些对进行排名。发现:除了n-gram袋之类的传统功能外,我们还将使用更有效的方面,包括单词嵌入,问题类别和。

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