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Identifying intention posts in discussion forums using multi-instance learning and multiple sources transfer learning

机译:使用多实例学习和多个来源转移学习识别讨论论坛的意图帖子

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This paper proposes a novel method for identifying intention posts in discussion forums. The main problem of identifying intention posts in discussion forums is that there exist a few intention sentences even in a post expressing an intention. That is, an intention post consists of a few intention sentences and a number of non-intention sentences, while non-intention posts have only non-intention sentences. Therefore, multi-instance learning which regards a post as a bag and the sentences in the post as instances of the bag is adopted as a solution to this problem. One distinct characteristic of the posts is that the ways of expressing an intention are similar across domains. Thus, we incorporate a multiple sources transfer learning into the multi-instance learning. As a result, the multi-instance learning is enhanced by leveraging knowledge of expressing intentions from multiple source domains. Through a set of experiments, it is proven that the proposed method is effective at identifying intention posts in discussion forums.
机译:本文提出了一种在讨论论坛中识别意向职位的新方法。在讨论论坛中识别意图帖子的主要问题是即使在表达意图的帖子中,也存在一些意图句子。也就是说,意图邮政包括一些意图句子和许多非意图句子,而非意图员额只有无意的判决。因此,将帖子作为袋子的多实例学习和作为袋子的句子中的句子被用作此问题的解决方案。帖子的一个不同特征是表达意图的方式在域中是类似的。因此,我们将多个源转移学习纳入多实例学习。因此,通过利用来自多个源域的意图的知识来增强多实例学习。通过一系列实验,证明该方法在识别论坛中识别意向职位是有效的。

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