Abstract
The discovery of association rules in large databases is considered an interesting and important research problem. Recently, different aspects of the problem have been studied, and several algorithms have been presented in the literature, among others in [3,8,9]. A time pattern association rule is an association rule that holds a specific time interval. For example, bread and coffee are frequently sold together in morning hours, or mooncake, lantern and candle are often sold before Mid-autumn Festival. This paper extends the a priori algorithm and develops the optimization technique for mining time pattern association rules.
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Thuan, N.D. (2010). Mining Time Pattern Association Rules in Temporal Database. In: Sobh, T. (eds) Innovations and Advances in Computer Sciences and Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3658-2_2
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DOI: https://doi.org/10.1007/978-90-481-3658-2_2
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