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Building ontology for different emotional contexts and multilingual environment in opinion mining

机译:在意见挖掘中为不同的情感环境和多语言环境建立本体

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With the explosive growth of various social media applications, individuals and organizations are increasingly using their contents (e.g. reviews, forum discussions, blogs, micro-blogs, comments, and postings in social network sites) for decision-making. These contents are typical big data. Opinion mining or sentiment analysis focuses on how to extract emotional semantics from these big data to help users to get a better decision. That is not an easy task, because it faces many problems, such as different context may make the meaning of the same word change variously, at the same time multilingual environment restricts the full use of the analysis results. Ontology provides knowledge about specific domains that are understandable by both the computers and developers. Building ontology is mainly a useful first step in providing and formalizing the semantics of information representation. We proposed an ontology DEMLOnto based on six basic emotions to help users to share existed information. The ontology DEMLOnto would help in identifying the opinion features associated with the contextual environment, which may change along with applications. We built the ontology according to ontology engineering. It was developed on the platform Protege by using OWL2.
机译:随着各种社交媒体应用的爆炸性增长,个人和组织越来越多地使用其内容(例如评论,论坛讨论,博客,微博,评论和社交网站上的帖子)进行决策。这些内容是典型的大数据。观点挖掘或情感分析专注于如何从这些大数据中提取情感语义,以帮助用户做出更好的决策。这不是一件容易的事,因为它面临许多问题,例如不同的上下文可能会使同一单词的含义发生多种变化,同时多语言环境限制了分析结果的充分利用。本体提供有关计算机和开发人员均可理解的特定域的知识。建立本体主要是提供和形式化信息表示语义的有用的第一步。我们提出了一种基于六种基本情感的本体DEMLOnto,以帮助用户共享现有信息。本体DEMLOnto将有助于识别与上下文环境相关联的意见特征,这些特征可能随应用程序而变化。我们根据本体工程构建了本体。它是使用OWL2在Protege平台上开发的。

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