Results 151 to 160 of about 530 (210)
Actionable Combined High Utility Itemset Mining
Proceedings of the AAAI Conference on Artificial Intelligence, 2015 The itemsets discovered by traditional High Utility Itemsets Mining (HUIM) methods are more useful than frequent itemset mining outcomes; however, they are usually disordered and not actionable, and sometime accidental, because the utility is the only judgement and no relations among itemsets are considered.
Jingyu Shao +3 more
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High-utility and diverse itemset mining
Applied Intelligence, 2021High-utility Itemset Mining (HUIM) finds patterns from a transaction database with their utility no less than a user-defined threshold. The utility of an itemset is defined as the sum of the utilities of its items. The utility notion enables a data analyst to associate a profit score with each item and thereof to a pattern. We extend the notion of high-
Amit Verma +4 more
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International Journal of Information Technology & Decision Making, 2010
High utility itemsets mining identifies itemsets whose utility satisfies a given threshold. It allows users to quantify the usefulness or preferences of items using different values. Thus, it reflects the impact of different items. High utility itemsets mining is useful in decision-making process of many applications, such as retail marketing and Web ...
Ying Liu 0039 +4 more
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High utility itemsets mining identifies itemsets whose utility satisfies a given threshold. It allows users to quantify the usefulness or preferences of items using different values. Thus, it reflects the impact of different items. High utility itemsets mining is useful in decision-making process of many applications, such as retail marketing and Web ...
Ying Liu 0039 +4 more
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Third IEEE International Conference on Data Mining, 2004
Traditional association rule mining algorithms only generate a large number of highly frequent rules, but these rules do not provide useful answers for what the high utility rules are. We develop a novel idea of top-K objective-directed data mining, which focuses on mining the top-K high utility closed patterns that directly support a given business ...
Raymond Chan +2 more
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Traditional association rule mining algorithms only generate a large number of highly frequent rules, but these rules do not provide useful answers for what the high utility rules are. We develop a novel idea of top-K objective-directed data mining, which focuses on mining the top-K high utility closed patterns that directly support a given business ...
Raymond Chan +2 more
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Mining of high‐utility itemsets with negative utility
Expert Systems, 2018AbstractHigh‐utility itemset (HUI) mining is an important tasks during data mining. Recently, many algorithms have been proposed to discover HUIs. Most of the algorithms work only for itemsets with positive utility values. However, in the real world, items are found with both positive and negative utility values.
Kuldeep Singh 0003 +3 more
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Vertical mining for high utility itemsets
2012 IEEE International Conference on Granular Computing, 2012Recently, high utility itemsets mining becomes one of the most important research issues in data mining due to its ability to consider different profit values for every item. In the past studies, most algorithms generate high utility itemsets from a set of transactions in horizontal data format.
Wei Song 0004, Yu Liu, Jinhong Li
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Mining high average-utility itemsets
2009 IEEE International Conference on Systems, Man and Cybernetics, 2009The average utility measure is adopted in this paper to reveal a better utility effect of combining several items than the original utility measure. A mining algorithm is then proposed to efficiently find the high average-utility itemsets. It uses the summation of the maximal utility among the items in each transaction including the target itemset as ...
Tzung-Pei Hong +2 more
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Incremental High Fuzzy Utility Itemset Mining
Proceedings of the 9th Multidisciplinary International Social Networks Conference, 2022 In the field of data mining, frequent-pattern mining is used for handling binary databases. Utility mining addresses this limitation by considering item utilities and quantities when discovering high utility itemsets. In addition, the fuzzy-set theory is
Tzung-Pei Hong +3 more
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High average-utility itemsets mining: a survey
Applied Intelligence, 2021HUIM (High utility itemsets mining) is a sub-division of data mining dealing with the task to obtain promising patterns in the quantitative datasets. A variant of HUIM is to discover the HAUIM (High average-utility itemsets mining) where average-utility measure is used to obtain the utility of itemsets.
Kuldeep Singh 0003 +2 more
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A Visualizer for High Utility Itemset Mining
2014 IEEE 17th International Conference on Computational Science and Engineering, 2014Mining high utility item sets is one of the most important research issues in data mining owing to its ability to consider nonbinary frequency values of items in transactions and different profit values for each item. Although several studies have been carried out, current methods present the mined results in the form of textual lists for users, which ...
Wei Song 0004, Mingyuan Liu
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