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Efficient algorithms to mine concise representations of frequent high utility occupancy patterns [PDF]
Applied intelligence (Boston)Identifying all frequent high utility occupancy itemsets (FHUOIs) in a quantitative transaction dataset is a new trend in data mining. By combining both factors of frequency and utility occupancy, these patterns are more suitable for several applications
Dương, Văn Hải, Phạm, Quang Huy
core +2 more sources
A Survey of Correlated High Utility Pattern Mining
IEEE Access, 2021 Pattern mining is an unsupervised data mining approach aims to find interesting patterns that can be used to support decision-making. High Utility Pattern Mining (HUPM) aims to extract patterns having high utility or importance which has broad ...
Rashad S. Almoqbily +2 more
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High-Utility Semantic Trajectory Pattern Mining for Security System [PDF]
Jisuanji gongcheng, 2023 In security systems，transforming a large number of collected target trajectories into semantic trajectories and mining their frequency patterns are helpful in analyzing target behavior patterns，identifying hazard sources，and enhancing internal prevention
FU Jiahao, YANG Jiayi, LI Aiguo
doaj +1 more source
Efficient Approach for Damped Window-Based High Utility Pattern Mining With List Structure
IEEE Access, 2020 Traditional pattern mining is designed to handle binary database that assume all items in the database have same importance, there is a limitation to recognize accurate information from real-world databases using traditional method. To solve this problem,
Hyoju Nam +5 more
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Discovering Approximate and Significant High-Utility Patterns from Transactional Datasets
Journal of Mathematics, 2022 Mining high-utility pattern (HUP) on transactional datasets has been widely discussed, and various algorithms have been introduced to settle this problem. However, the time-space efficiency of the algorithms is still limited, and the mining system cannot
Huijun Tang +3 more
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Scalable Sampling for High Utility Patterns [PDF]
BigData Congress [Services Society]Discovering valuable insights from data through meaningful associations is a crucial task. However, it becomes challenging when trying to identify representative patterns in quantitative databases, especially with large datasets, as enumeration-based ...
Lamine Diop, Marc Plantevit
semanticscholar +1 more source
A Data-Driven Approach for Twitter Hashtag Recommendation
IEEE Access, 2020 This paper addresses the hashtag recommendation problem using high average-utility pattern mining. We introduce a novel framework called PM-HRec (Pattern Mining for Hashtag Recommendation). It consists of two main stages.
Asma Belhadi +3 more
doaj +1 more source
A New Algorithm for High Average-utility Itemset Mining [PDF]
Journal of Artificial Intelligence and Data Mining, 2019 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.
A. Soltani, M. Soltani
doaj +1 more source
IEEE Access, 2021 Utility-pattern mining in data has received a lot of attention from the knowledge discovery in database (KDD) community due to its high potential for many applications such as finance, biomedicine, manufacturing, e-commerce, and social media.
Jerry Chun-Wei Lin +3 more
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High average-utility sequential pattern mining based on uncertain databases
, 2020 emergence and proliferation of the internet of things (IoT) devices have resulted in the generation of big and uncertain data due to the varied accuracy and decay of sensors and their different sensitivity ranges.
Zhang, Ji +4 more
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