文章基本信息

标题：Parallel Approaches of Utility Mining for Big Data
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作者：Vandna Dahiya
期刊名称：Webology
印刷版ISSN：1735-188X
出版年度：2020
卷号：17
期号：2
页码：31-43
DOI：10.14704/WEB/V17I2/WEB17014
出版社：University of Tehran
摘要：Utility Itemset Mining (UIM) is a fundamental technique to find out various itemsets with interestingness measures in addition to their quantity. It helps in finding valuable items that cannot be tracked with frequent itemset mining. There are many techniques to mine the itemsets based on their utilities, but the need of the hour is to mine them from larger datasets. This paper presents a brief overview of various approaches for utility mining, which mine using the parallel framework to enhance the pace of computation. The paper is concluded with a discussion on various challenges and openings in the field of parallel mining and provides away for further development of the prevailing methodologies of big data.
关键词：Utility Mining; Big Data; Spark; Parallel Computing;