An efficient colossal closed itemset mining algorithm for a dataset with high dimensionality
نویسندگان
چکیده
منابع مشابه
An Efficient Algorithm for Mining Closed High Utility Itemset
Mining of High utility itemsets refers to discovering sets of data items that have high utilities. In recent years the high utility itemsets mining has extensive attentions due to the wide applications in various domains like biomedicine and commerce. Extraction of high utility itemsets from database is very problematic task. The formulated high utility itemset degrades the efficiency of the mi...
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High utility itemset mining (HUIM) is a new emerging field in data mining which has gained growing interest due to its various applications. The goal of this problem is to discover all itemsets whose utility exceeds minimum threshold. The basic HUIM problem does not consider length of itemsets in its utility measurement and utility values tend to become higher for itemsets containing more items...
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The set of frequent closed itemsets uniquely determines the exact frequency of all itemsets, yet it can be orders of magnitude smaller than the set of all frequent itemsets. In this paper we present CHARM, an efficient algorithm for mining all frequent closed itemsets. It enumerates closed sets using a dual itemset-tidset search tree, using an efficient hybrid search that skips many levels. It ...
متن کاملEFIM: A Highly Efficient Algorithm for High-Utility Itemset Mining
High-utility itemset mining (HUIM) is an important data mining task with wide applications. In this paper, we propose a novel algorithm named EFIM (EFficient high-utility Itemset Mining), which introduces several new ideas to more efficiently discovers high-utility itemsets both in terms of execution time and memory. EFIM relies on two upper-bounds named sub-tree utility and local utility to mo...
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The set of frequent closed itemsets determines exactly the complete set of all frequent itemsets and is usually much smaller than the latter. This paper proposes an improved algorithm for mining frequent closed itemsets. Firstly, the index array is proposed, which is used for discovering those items that always appear together. Then, by using bitmap, an algorithm for computing index array is pr...
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ژورنال
عنوان ژورنال: Journal of King Saud University - Computer and Information Sciences
سال: 2020
ISSN: 1319-1578
DOI: 10.1016/j.jksuci.2020.04.008