Infusing social data analytics into Future Internet applications for manufacturing

Evmorfia Biliri, Michael Petychakis, Iosif Alvertis, Fenareti Lampathaki, S. Koussouris, D. Askounis
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引用次数: 6

Abstract

Today, a new age of engagement and collaboration has emerged with the proliferation of usergenerated content in social networks and generally the Web 2.0, rendering it particularly difficult for enterprises to monitor and act upon all content following conventional data mining methodologies. In this paper, we present our approach for a Future Internet enabler (FITMAN Anlzer) that provides automated, social data analytics and aims at assisting enterprises in becoming more tuned to their customer needs and gaining insights into current and future trends to early embed them into product design. The FITMAN Anlzer implementation is domainindependent and allows any manufacturer to effectively train it based on his needs and create personalized reports to timely capture the right information. Our methodology includes trend analytics, polarity detection through machine learning, data querying through flexible reports and finally informative charts to visualize the results in order to help companies in their decision making procedures.
将社会数据分析融入未来制造业的互联网应用
今天,随着社交网络和Web 2.0中用户生成内容的激增,出现了一个参与和协作的新时代,这使得企业按照传统的数据挖掘方法监视所有内容并对其采取行动变得特别困难。在本文中,我们介绍了未来互联网推动者(FITMAN Anlzer)的方法,该方法提供自动化的社交数据分析,旨在帮助企业更加适应客户需求,并获得对当前和未来趋势的洞察,以便尽早将其嵌入产品设计中。FITMAN分析仪的实现是独立于领域的,允许任何制造商根据他的需求有效地培训它,并创建个性化的报告,以及时捕获正确的信息。我们的方法包括趋势分析,通过机器学习进行极性检测,通过灵活的报告进行数据查询,最后通过信息图表将结果可视化,以帮助公司进行决策过程。
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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