文章基本信息

标题：Data Mining Application using Association Rule Mining ECLAT Algorithm Based on SPMF
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作者：Jason Reynaldo ; David Boy Tonara
期刊名称：MATEC Web of Conferences
电子版ISSN：2261-236X
出版年度：2018
卷号：164
DOI：10.1051/matecconf/201816401019
语种：English
出版社：EDP Sciences
摘要：Data mining is an important research domain that currently focused on knowledge discovery database. Where data from the database are mined so that information can be generated and used effectively and efficiently by humans. Mining can be applied to the market analysis. Association Rule Mining (ARM) has become the core of data mining. The search space is exponential in the number of database attributes and with millions of database objects the problem of I/O minimization becomes paramount. To get the information and the data such as, observation of the master data storage systems and interviews were done. Then, ECLAT algorithm is applied to the open-source library SPMF. In this project, this application can perform data mining assisted by open source SPMF with determined writing format of transaction data. It successfully displayed data with 100 % success rate. The application can generate a new easier knowledge which can be used for marketing the product.
关键词：enAssociation rule miningData miningECLATMining librarySPMF