Music interest is diverse yet enticing to be a part of knowledge discovery. It influences how people feel, study, work, etc. A lot things are considered in producing brand new music with its correlation genre. We have already collected the dataset that we can utilize this research, which history every song listened by several users total 20.000 records from million dataset. This study implement...

This work discusses the problem of generating association rules from a set of transactions in a relational database, taking performance and accuracy of found results as the essential aspects for comparing association mining algorithms. We do a critical analysis of two previously existing methods, Apriori and FP-growth, emphasizing their strengths and weaknesses; and based on this analysis, we p...

Association rule discovery plays an important role in knowledge discovery and data mining, and efficiency is especially crucial for an algorithm finding frequent itemsets from a large database. Many methods have been proposed to solve this problem. In addition, parallel computing has been a popular trend, such as on cloud platform, grid system or multicore platform. In this paper, a high effici...