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A Multi-Source Big Data Framework for Capturing and Analyzing Customer Feedback

机译:用于捕获和分析客户反馈的多源大数据框架

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Big Data refers to the highly growing digital data collections that involve data with different formats, including structured, semi-structured, and unstructured datasets. Analyzing these combinations requires capabilities beyond the traditional database management systems' abilities. Among most sources of big data appears e-markets and social media platforms as significant contributors. This distinction is due to its features that facilitate consumers to express their views or opinions about specific products and services. Customer reviews and ratings become a significant resource for both consumers and firms regarding their plentiful and valuable knowledge. The proposed work introduces a big data framework to analyze such reviews and ratings, starting with data collection from different sources. Followed by integrating the collected data, which comes in different formats, toward the further processing phase. Finally, the analysis and visualization steps to draw the conclusions. Our work was tested on real data collected from active web resources.
机译:大数据是指高度生长的数字数据集合,涉及具有不同格式的数据,包括结构化,半结构和非结构化数据集。分析这些组合需要超出传统数据库管理系统的能力的能力。在大多数大数据来源中,作为重要贡献者,将出现电子市场和社交媒体平台。这种区别是由于其特征,促进了消费者表达有关特定产品和服务的观点或意见。客户评论和评级成为消费者和公司的重要资源,了解他们丰富和宝贵的知识。拟议的工作介绍了一个大数据框架,分析了从不同来源的数据收集开始的评论和评级。然后通过将收集的数据集成到进一步的处理阶段以不同的格式进行集成。最后,分析和可视化步骤得出结论。我们的工作是在从活动Web资源收集的实际数据上进行测试的。

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