Abstract
Data mining aims to efficiently discover previously unknown knowledge from large databases. It is highly demanding in numerous real-life applications, such as marketing strategy, financial forecast, etc. One of the fundamental problems in the area is the efficient computation of association rules. In this paper, we shall investigate this problem in a distributed database. Particularly, we will present an efficient distributed algorithm for mining distributed association rules. Our experiment results suggest that the proposed algorithm outperforms the existing distributed algorithms. Further, we also study a distributed version of the problem of association rules; and extend our algorithm to solve this new problem.
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Li, Y., Lin, X., Tsang, CP. (2000). An Efficient Distributed Algorithm for Computing Association Rules. In: Lu, H., Zhou, A. (eds) Web-Age Information Management. WAIM 2000. Lecture Notes in Computer Science, vol 1846. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45151-X_10
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DOI: https://doi.org/10.1007/3-540-45151-X_10
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