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Text Mining for Opinion Target Detection

机译:用于意见目标检测的文本挖掘

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摘要

This article presents a text mining approach based on linguistic knowledge to automatically detect opinion targets in relation with topic elements, for competitive intelligence. The identification of opinions and sentiments expressed in texts is currently studied a lot, but few works are focused on the identification of opinions whose target is associated to a predefined topic. We present in a first time the information detection task with linguistic patterns, and a state of the art on opinion detection and opinion targets detection. Then we describe the French corpora: one contains transcription of telephone requests related to Energy, the other contains extracts of internet forum related to Video Games. Next we detail the linguistic knowledge used to annotate those texts. The knowledge is based on the identification of explicit relations between topic and opinion ("Transformers is great") and on the identification of implicit opinions ("they intervene quickly"). At last, an example of result is presented, as a first evaluation.
机译:本文提出了一种基于语言知识的文本挖掘方法,可以自动检测与主题元素相关的意见目标,从而获得竞争情报。当前对文本中表达的观点和情感的识别进行了很多研究,但是很少有工作专注于识别目标与预定义主题相关的观点。我们将首次提出具有语言模式的信息检测任务,以及意见检测和意见目标检测的最新技术。然后我们描述法国语料库:一种包含与能源有关的电话请求的抄录,另一种包含与视频游戏有关的互联网论坛的摘录。接下来,我们详细说明用于注释这些文本的语言知识。该知识基于对主题和观点之间明确关系的识别(“变形金刚很棒”)和对隐含观点的识别(“它们迅速介入”)。最后,给出了一个结果示例,作为第一次评估。

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