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Data Mining Application using Association Rule Mining ECLAT Algorithm Based on SPMF

机译:基于SPMF的关联规则挖掘ECLAT算法在数据挖掘中的应用

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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.
机译:数据挖掘是当前专注于知识发现数据库的重要研究领域。从数据库中挖掘数据的地方,以便人类可以有效地生成和使用信息。挖掘可以应用于市场分析。关联规则挖掘(ARM)已成为数据挖掘的核心。搜索空间的数据库属性数量成指数增长,并且随着数百万个数据库对象的出现,I / O最小化的问题变得至关重要。为了获得信息和数据,例如完成了对主数据存储系统的观察和访谈。然后,将ECLAT算法应用于开源库SPMF。在此项目中,此应用程序可以使用确定的交易数据写入格式,在开源SPMF的辅助下执行数据挖掘。它成功显示了数据,成功率为100%。该应用程序可以生成可用于营销产品的新的更轻松的知识。

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