Abstract: Existing algorithms for utility mining are inadequate on datasets with high dimensions or long patterns. This paper proposes a hybrid method, ...
Existing algorithms for utility mining are inadequate on datasets with high dimensions or long patterns. This paper proposes a hybrid method,.
A hybrid method, which is composed of a row enumeration algorithm and a column enumeration algorithms, to discover high utility itemsets from two directions ...
Existing algorithms for utility mining are inadequate on datasets with high dimensions or long patterns. This paper proposes a hybrid method, ...
Jul 1, 2019 · High-Utility Itemset (HUI) mining is an important data-mining task which has gained popularity in recent years due to its applications in ...
May 9, 2015 · In recent years, extensive studies have been conducted on high utility itemsets (HUI) mining with wide applications.
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This paper formulates the task of targeted mining of the top- high-utility itemsets and proposes an efficient algorithm called TMKU based on the TargetUM ...
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High utility itemset mining is an important data mining problem which considers profit factors besides quantity from the transactional database.
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Abstract High utility pattern mining is an emerging data science task, which consists of discovering patterns having a high importance in databases.
Existing algorithms for high-utility itemsets mining are column enumeration based, adopting an Apriorilike candidate set generation-and-test approach, and thus ...