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This paper proposed an algorithm of mining association rules with constraints based on immune genetic algorithm, which for the anti-monotone and monotone constraint conditions. This algorithm was inspired by the fundamentals of the biological immune system which the process of B-cells to produce the optimal antibody under the T-cells constraint. From this metaphor, firstly, according the different...
OLAP query is an efficient way to gain quick insight into big data. Spark is a fast and general engine for big data processing, which supports interactive OLAP queries. Nevertheless, as a general engine, there are many parameters that affect the performance of the Spark, and thus it is necessary to study the appropriate setting in order to gain better performance on a specific scenario. In this paper,...
Clustering plays an important role in data mining, as it is used by many applications as a preprocessing step for data analysis. Traditional clustering focuses on grouping similar objects, while two-way co-clustering can group dyadic data (objects as well as their attributes) simultaneously. In this research, we apply two-way co-clustering to the analysis of online advertising where both ads and users...
This paper applies rough set theory to recognition system for image defect, and designs a decision algorithm on rough set suitable for image defect recognition. Firstly, the image is made regionalization and sequential discrete set is proposed, the continuous attributes of image is discretized. Then the decision table model on discrete condition attributes and decision attributes is constructed. Further...
Generating decision rules is one of the most important data mining areas which ldquorough set data analysis(RSDA)rdquo can address. Generally, for the same expression, the shorter the rules are, the more effectively the system performances. Considering of this, this paper provides a new heuristic algorithm named ldquoshort first extraction (SFE)rdquo based on the classical rough set theory, for rules...
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