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A retrieval model for question in community question answering system

机译:社区问答系统中问题的检索模型

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Studies of Community-based question and answer services (cQA) have grown to be one of the emerging trends in Web information services. And one of the main tasks is to retrieve similar questions. To identify the fact that some questions with different expressions though may indeed have the same, or very similar, meaning, the similar questions are defined in syntactic, semantic and pragmatic aspects according to user retrieval intention. Five models including Language Model, Translation-based Language Model, Parser-based model, LDA and WordNet source-based model are selected as baselines. Integrated models which linearly combine WordNet, Stanford Parser and Language Model and further weighted by syntactic feature are proposed to integrate features of the three aspects. Experiment results show that our integrated models perform better than the basic models, especially when the linear combination of the WordNet model and the Stanford Parser model is weighted by syntactic information with proper noun phrases as representative. The integrated models are further verified by logistic analysis.
机译:基于社区的问答服务(cQA)的研究已成为Web信息服务中新兴的趋势之一。主要任务之一是检索类似的问题。为了确定一些事实,尽管表达不同的某些问题的确具有相同或非常相似的含义,但根据用户的检索意图,在句法,语义和语用方面定义了相似的问题。选择了五个模型,包括语言模型,基于翻译的语言模型,基于解析器的模型,LDA和基于WordNet源的模型。提出了将WordNet,Stanford Parser和Language Model线性组合并进一步通过句法特征进行加权的集成模型,以集成这三个方面的特征。实验结果表明,我们的集成模型比基本模型具有更好的性能,特别是当WordNet模型和Stanford Parser模型的线性组合以适当的名词短语为代表的句法信息加权时。通过逻辑分析进一步验证了集成模型。

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