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QU-BIGIR at SemEval 2017 Task 3: Using Similarity Features for Arabic Community Question Answering Forums

机译:QU-BIGIR在SemEval 2017上的任务3:对阿拉伯社区问题回答论坛使用相似功能

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In this paper, we describe our QU-BIGIR system for the Arabic subtask D of the SemEval 2017 Task 3. Our approach builds on our participation in the past version of the same subtask. This year, our system uses different similarity features that encodes lexical and semantic pairwise similarity of text pairs. In addition to well-known similarity measures such as cosine similarity, we use other measures based on the summary statistics of word embedding representation for a given text. To rank a list of candidate question-answer pairs for a given question, we train a linear SVM classifier over our similarity features. Our best resulting run came second in subtask D with a very competitive performance to the first-ranking system.
机译:在本文中,我们描述了SemEval 2017任务3的阿拉伯文子任务D的QU-BIGIR系统。我们的方法基于我们对同一子任务的过去版本的参与。今年,我们的系统使用了不同的相似性功能,它们对文本对的词汇和语义成对相似性进行编码。除了众所周知的相似度度量(例如余弦相似度)外,我们还基于给定文本的词嵌入表示的摘要统计量,使用其他度量。为了对给定问题的候选问题-答案对列表进行排名,我们在相似性特征上训练了线性SVM分类器。我们获得的最佳结果是子任务D中的第二名,其性能与第一名的系统非常有竞争力。

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