数据。频繁模式的信息和知识可视化

Calvin S. H. Hoi, C. Leung, Adam G. M. Pazdor
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引用次数: 2

摘要

在当今快速发展的信息技术世界中,数据不断增长。大数据是指数据量大、速度快、种类多、准确性高低不一的数据流。这些大数据中隐含着以前未知的、但有价值的信息和知识。由于数据挖掘等技术可以发现大量的信息和知识,因此验证和可视化数据挖掘结果是一个挑战。为了验证数据,以便更好地在估计和预测中进行数据聚合,并建立可信的人工智能,需要可视化模型和数据挖掘策略的协同作用。因此,在本文中,我们提出了一种针对频繁出现的模式的数据、信息和知识可视化的解决方案。我们的解决方案将文本频繁模式转换为具有重要信息的等价但更易于理解的图形表示形式:频率分布。该解决方案揭示了从各种应用程序和服务中的事务数据库中挖掘的有趣信息和有价值的知识。用实际数据进行的评估证明了我们的解决方案在将发现的频繁模式的数据和信息可视化方面的有效性和实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data. Information and Knowledge Visualization for Frequent Patterns
In the current fast information-technological world, data are kept growing bigger. Big data refer to the data flow of huge volume, high velocity, wide variety, and different levels of veracity. Embedded in these big data are implicit, previously unknown, but valuable information and knowledge. With huge volumes of information and knowledge that can be discovered by techniques like data mining, a challenge is to validate and visualize the data mining results. To validate data for better data aggregation in estimation and prediction and for establishing trustworthy artificial intelligence, the synergy of visualization models and data mining strategies are needed. Hence, in this paper, we present a solution for data, information and knowledge visualization for frequently occurring patterns. Our solution transforms textual frequent patterns into their equivalent but more comprehendible graphical representations with important information: frequency distribution. The solution reveals interesting information and valuable knowledge mined from the transactional databases in various applications and services. Evaluation with real-life data demonstrates the effectiveness and practicality of our solution in visualizing data and information of the discovered frequent patterns.
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