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A Sentiment Analysis Classification Approach to Assess the Emotional Content of Photographs

机译:一种情感分析分类方法,评估照片的情绪内容

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The integration of Ambient Intelligence and Sentiment Analysis provides mutual benefits. On the one hand, Sentiment Analysis may enable developing interfaces providing a more natural interaction with human-computer interfaces. On the other, AmI enables using context-awareness information to enhance the performance of the system, achieving a more efficient and proactive human-machine communication that can be dynamically adapted to the user's state and the status of the environment. In this paper, we describe a novel Sentiment Analysis approach combining a lexicon-based model for specifying the set of emotions and a statistical methodology to identify the most relevant topics in the document that are the targets of the sentiments. Our proposal also includes an heuristic learning method that allows improving the initial knowledge considering the users' feedback. We have integrated the proposed Sentiment Analysis approach into an Android-based mobile App that automatically assigns sentiments to pictures taking into account the description provided by the users.
机译:环境智能与情感分析的整合提供了互利。一方面,情绪分析可以开发开发接口,提供与人机接口更自然的交互。另一方面,AMI使使用上下文识别信息来增强系统的性能,实现更高效和主动的人机通信,可以动态地适应用户的状态和环境的状态。在本文中,我们描述了一种新的情绪分析方法,其组合基于词汇的模型,用于指定情感集和统计方法,以确定文档中的最相关的主题是情绪的目标。我们的提案还包括一种启发式学习方法,可以提高考虑用户反馈的初始知识。我们已经将建议的情感分析方法集成到基于Android的移动应用程序中,以考虑用户提供的描述,自动为图片分配情绪。

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