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Using Formulaic Expressions in Writing Assistance Systems

机译:在写作辅助系统中使用公式表达式

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Formulaic expressions (FEs) used in scholarly papers, such as 'there has been little discussion about', are helpful for non-native English speakers. However, it is time-consuming for users to manually search for an appropriate expression every time they want to consult FE dictionaries. For this reason, we tackle the task of semantic searches of FE dictionaries. At the start of our research, we identified two salient difficulties in this task. First, the paucity of example sentences in existing FE dictionaries results in a shortage of context information, which is necessary for acquiring semantic representation of FEs. Second, while a semantic category label is assigned to each FE in many FE dictionaries, it is difficult to predict the labels from user input, forcing users to manually designate the semantic category when searching. To address these difficulties, we propose a new framework for semantic searches of FEs and propose a new method to leverage both existing dictionaries and domain sentence corpora. Further, we expand an existing FE dictionary to consider building a more comprehensive and domain-specific FE dictionary and to verify the effectiveness of our method.
机译:学术论文中使用的公式化表达(FE),例如“鲜有讨论”,对于非英语母语的人很有帮助。但是,每次用户要查询FE词典时,手动搜索适当的表达式都是很耗时的。因此,我们要处理有限元词典的语义搜索任务。在研究开始时,我们确定了此任务中的两个显着困难。首先,现有FE词典中例句的匮乏导致上下文信息不足,这对于获取FE的语义表示是必不可少的。其次,尽管在许多FE词典中为每个FE分配了一个语义类别标签,但是很难根据用户输入来预测标签,从而迫使用户在搜索时手动指定语义类别。为了解决这些困难,我们提出了一种用于有限元语义搜索的新框架,并提出了一种利用现有字典和领域句子语料库的新方法。此外,我们扩展了现有的有限元词典,以考虑构建更全面和特定领域的有限元词典并验证我们方法的有效性。

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