Abstract
Mining association rules have been one of the research focuses in data mining; an improved algorithm based on graph is presented for discovering various types of association rules in this paper. We introduce the original algorithm based on graph; on that basis, we improve it according to the idea of partition and compression. Firstly, the association graph constructed is partitioned into many association subgraphs. Secondly, we compress these subgraphs and mine frequent itemsets respectively which will not influence each other in different parts. In the end, the improved algorithm is compared with the original one in performance.
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Jiang, H., He, Y., Wan, W. (2014). An Improved Algorithm for Mining Association Rules Based on Partitioned and Compressed Association Graph. In: Patnaik, S., Li, X. (eds) Proceedings of International Conference on Computer Science and Information Technology. Advances in Intelligent Systems and Computing, vol 255. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1759-6_75
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DOI: https://doi.org/10.1007/978-81-322-1759-6_75
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-1758-9
Online ISBN: 978-81-322-1759-6
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