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Big Data Visualisation and Visual Analytics for Music Data Mining

机译:音乐数据挖掘的大数据可视化和可视化分析

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As high volumes of a wide variety of valuable data of different veracities can be easily generated or collected at a high velocity nowadays, big data visualisation and visual analytics are in demand in various real-life applications. Musical data are examples of big data. Embedded in these big data are useful information and valuable knowledge. Many existing big data mining algorithms return useful information and valuable knowledge in textual or tabular forms. Knowing that "a picture is worth a thousand words", big data visualisation and visual analytics are also in demand. In this paper, we present a system for visualising and analysing big data. In particular, our system focuses on the big data science task of the discovery and exploration of frequent patterns (i.e., collections of items that frequently occurring together) from musical data. Evaluation results show the applicability of our system in big data visualisation and visual analytics for music data mining.
机译:如今,由于可以轻松快速地高速生成或收集大量具有不同准确性的有价值的数据,因此在各种实际应用中都需要大数据可视化和可视化分析。音乐数据就是大数据的例子。有用的信息和宝贵的知识嵌入在这些大数据中。许多现有的大数据挖掘算法以文本或表格形式返回有用的信息和有价值的知识。知道“一张图片值得一千个单词”,因此也需要大数据可视化和可视化分析。在本文中,我们提出了一种可视化和分析大数据的系统。特别是,我们的系统专注于大数据科学任务,即从音乐数据中发现和探索频繁模式(即,经常一起出现的物品的集合)。评估结果表明我们的系统在音乐数据挖掘的大数据可视化和视觉分析中的适用性。

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