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An NLP Framework for Interpreting Implicit and Explicit Opinions in Text and Dialog (Academic Keynote Talk)

机译:用于解释文本和对话框中的隐式和显式意见的NLP框架(学术主题演讲)

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While previous sentiment analysis research has concentrated on the interpretation of explicitly stated opinions and attitudes, this work addresses the computational study of a type of opinion implicature (i.e., opinion-oriented inference) in text and dialog. This talk will describe a framework for representing and analyzing opinion implicatures which promises to contribute to deeper automatic interpretation of subjective language. In the course of understanding implicatures, the system recognizes implicit sentiments (and beliefs) toward various events and entities in the sentence, often attributed to different sources (holders) and of mixed polarities; thus, it produces a richer interpretation than is typical in opinion analysis.
机译:虽然以前的情感分析研究集中于对明确陈述的观点和态度的解释,但这项工作着眼于对文本和对话中一种观点含意(即观点导向的推论)的计算研究。本演讲将描述一个表示和分析观点含意的框架,该框架有望有助于对主观语言的更深层次的自动解释。在理解隐含含义的过程中,系统会识别出对句子中各种事件和实体的隐含情绪(和信念),这些事件和实体通常归因于不同的来源(持有人)和混合极性。因此,它产生的解释比意见分析中的典型解释更丰富。

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