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Ontology-Guided Approach to Feature-Based Opinion Mining

机译：本体思路思路的本体论引导方法

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摘要

The boom of the Social Web has had a tremendous impact on a number of different research topics. In particular, the possibility to extract various kinds of added-value, informational elements from users' opinions has attracted researchers from the information retrieval and computational linguistics fields. However, current approaches to socalled opinion mining suffer from a series of drawbacks. In this paper we propose an innovative methodology for opinion mining that brings together traditional natural language processing techniques with sentimental analysis processes and Semantic Web technologies. The main goals of this methodology is to improve feature-based opinion mining by employing ontologies in the selection of features and to provide a new method for sentimental analysis based on vector analysis. The preliminary experimental results seem promising as compared against the traditional approaches.
机译：社交网络的繁荣对许多不同的研究主题产生了巨大影响。特别是，从用户意见中提取各种添加价值的可能性，从信息检索和计算语言学领域吸引了研究人员。然而，目前对被子意见挖掘的方法遭受了一系列缺点。在本文中，我们提出了一种旨在宣传挖掘的创新方法，这些方法将传统的自然语言处理技术汇集了一种感伤分析过程和语义网络技术。该方法的主要目标是通过在选择特征中使用本体和基于载体分析提供一种新的感伤分析方法来改善基于特征的意见挖掘。与传统方法相比，初步实验结果似乎很有前景。

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