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Association rules are adopted to discover the interesting relationship and knowledge in a large dataset. Knowledge may appear in terms of a frequent pattern discovered in a large number of production data. This knowledge can improve or solve production problems to achieve low cost production. To obtain knowledge and quality information, data mining can be applied to the manufacturing industry. In...
In this study, we present a novel approach to recommend the personalized book lists for the university members. Our approach consists of clustering the university members into different clusters based on their recent circulation activities and discovering the interest patterns of members in the cluster. In the first step, we clustered members sharing the common interests to the same cluster by using...
This paper presents an applied study in data mining and knowledge discovery. It aims at discovering patterns within historical students' academic and financial data at UST (University of Science and Technology) from the year 1993 to 2005 in order to contribute improving academic performance at UST. Results show that these rules concentrate on three main issues, students' academic achievements (successes...
In our study, we propose a Web information recommendation framework depending on user behaviors. It is different from traditional recommendation systems depending on single association rule or classification engine. It has an interactive interface with people who could adjust his access manner according to the requirements by himself. It differs from the system which needs each reader to indicate...
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