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In order to improve the efficiency of Apriori algorithm for mining frequent item sets, MH-Apriori algorithm was designed for big data to address the poor efficiency problem. MH-Apriori takes advantages of MapReduce and HBase together to optimize Apriori algorithm. Compared with the improved Apriori algorithm simply based on MapReduce framework, timestamp of HBase is utilized in this algorithm to avoid...
Rule engine, which acknowledges facts and draws conclusions by repeatedly matching facts with rules, is a good way of knowledge representation and inference. However, because of its low computational efficiency and the limitation of single machine's capacity, it cannot deal well with big data. As traditional MapReduce architecture can only address this problem in certain conditions, we have made some...
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