基于意见和语义关系的在线评论意见目标和意见词协同抽取

2018 Fifteenth International Conference on Wireless and Optical Communications Networks (WOCN) Pub Date : 2018-02-01 DOI:10.1109/WOCN.2018.8556134

Savitha Mathapati, S. ShreelekhaB., R. Tanuja, S. Manjula, K. Venugopal

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引用次数: 2

摘要

从在线评论中挖掘意见是获得产品整体情绪的基本步骤。词间意见关系的检测在意见目标(OT)和意见词(OW)提取中起着重要的作用。本文采用部分监督词对齐模型来寻找词间的意见关系。采用基于图的协同排序算法对每个OT和OW的置信度进行估计。提取置信度高于阈值的候选值作为最终的OT和OW。我们提出了一种考虑语义关系和意见关系的混合方法，从而实现细粒度意见目标和意见词的提取。这种语义关系和意见关系影响了OT和OW的置信度计算，提高了提取的精度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Co-extraction of Opinion Targets and Opinion Words from Online Reviews Based on Opinion and Semantic Relations

Mining opinions from online reviews is a fundamental step in obtaining the overall sentiment of a product. Detection of opinion relations among the words play an important role in the opinion target (OT) and opinion word (OW) extraction. In this paper, Partially Supervised Word Alignment Model is used to find opinion relations among words. Graph based co-ranking algorithm is used in estimating the confidence of each OT and OW. Candidates having confidence value higher than the threshold are extracted as final OT and OW. We propose a hybrid method that considers semantic relations along with opinion relations that results in fine grained opinion target (OT) and opinion word (OW) extraction. This semantic relations and opinion relations affects the confidence calculation of the OT and OW and improves the precision of extraction.

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来源期刊

2018 Fifteenth International Conference on Wireless and Optical Communications Networks (WOCN)

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