Multi-agent framework for social CRM: Extracting and analyzing opinions

F. Z. Ennaji, A. E. Fazziki, Hasna El Alaouiel El Abdallaoui, Abderrahmane Sadiq, M. Sadgal, D. Benslimane
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引用次数: 5

Abstract

Numerous studies have discussed the benefits of using social networks, even companies started to exploit the usefulness of this valuable information sources. Collecting social data then integrating them into a CRM (Customer Relationship Management) has led companies to understand the customer needs and therefore to improve the development process of their products or their services quality. In this work, we propose a multi-agent framework for analyzing extracted opinions from social media. In the development process, we were brought to consider the huge volumes of data (Big Data) and the response time. To do so, an architecture based on Map/Reduce analysis using Hadoop was made in order to perform the data refinement (classify or remove special words or delete the unvaluable reviews) and sentiment analysis (Sentigem). Finally, a study case using Twitter (Twitter4J API) as a data source, was made to verify the effectiveness of the proposed framework.
社交CRM的多代理框架:意见提取与分析
许多研究讨论了使用社交网络的好处,甚至公司也开始利用这种有价值的信息源的有用性。收集社会数据,然后将其集成到CRM(客户关系管理)中,这使公司了解客户需求,从而改进产品或服务质量的开发过程。在这项工作中,我们提出了一个多智能体框架来分析从社交媒体中提取的意见。在开发过程中,我们不得不考虑海量数据(大数据)和响应时间。为此,使用Hadoop构建了一个基于Map/Reduce分析的架构,以执行数据细化(分类或删除特殊单词或删除无价值评论)和情感分析(Sentigem)。最后,通过一个使用Twitter (Twitter4J API)作为数据源的研究案例来验证所提出框架的有效性。
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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