Abstract
The previous research in mining association rules pays no attention to finding rules from imprecise data, and the traditional data mining cannot solve the multi-policy-making problem. Furthermore, in this research, we incorporate association rules with rough sets and promote a new point of view in applications. The new approach can be applied for finding association rules, which has the ability to handle uncertainty combined with rough set theory. In the research, first, we provide new algorithms modified from Apriori algorithm and then give an illustrative example. Finally, give some suggestion based on knowledge management as a reference for future research.
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Liao, SH., Chen, YJ., Ho, SH. (2011). The Rough Set-Based Algorithm for Two Steps. In: Lu, BL., Zhang, L., Kwok, J. (eds) Neural Information Processing. ICONIP 2011. Lecture Notes in Computer Science, vol 7063. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24958-7_8
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DOI: https://doi.org/10.1007/978-3-642-24958-7_8
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