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The problem of mining frequent itemsets plays an essential role in mining association rules, but it is not necessary to mine all frequent itemsets, instead it is sufficient to mine the set of frequent closed itemsets, which is much smaller than the set of all frequent itemsets. In this paper, we present an efficient algorithm, FCI-Miner, for mining all frequent closed itemsets. It based on the improved...
Association rules are the main technique for data mining. Apriori algorithm is a classical algorithm of association rule mining. Lots of algorithms for mining association rules and their mutations are proposed on basis of apriori algorithm, but traditional algorithms are not efficient. For the two bottlenecks of frequent itemsets mining: the large multitude of candidate 2-itemsets, the poor efficiency...
To solve the problem of mining weighted frequent traversal patterns (WFTPs) with noisy weight information from weighted directed graph (WDG), an effective algorithm called SWFTPMiner (statistical theory-based weighted frequent traversal patterns miner) is developed. It first adopts statistical notion called confidence interval (CI) to delete the vertices with noisy weights from the traversal database...
Traditional text mining techniques have weak ability to provide associated relations with rich semantics that is a foundation of the intelligent browsing of topics, discovery of semantic community and precise personalized recommendation in current Web and Knowledge Grid, etc. In this paper we propose an algorithm to generate and calculate the associated relations and their strengths between documents...
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