Results 11 to 20 of about 2,623,624 (325)

Fuzzy high-utility pattern mining in parallel and distributed Hadoop framework

Information Sciences, 2021
Over the past decade, high-utility itemset mining (HUIM) has received widespread attention that can emphasize more critical information than was previously possible using frequent itemset mining (FIM). Unfortunately, HUIM is very similar to FIM since the
J. Wu, Gautam Srivastava, Min Wei, Unil Yun, Chun-Wei Lin   +4 more
semanticscholar   +3 more sources

Discovering high utility-occupancy patterns from uncertain data [PDF]

Information Sciences, 2021
Elsevier Information Sciences, 12 ...
Chien-Ming Chen, Lili Chen, Wensheng Gan, Lina Qiu, Weiping Ding   +4 more
openaire   +2 more sources

TKUS: Mining top-k high utility sequential patterns [PDF]

Information Sciences, 2021
Preprint, 22 ...
Zhang, Chunkai, Du, Zilin, Gan, Wensheng, Yu, Philip S.   +3 more
openaire   +2 more sources

Efficient Algorithm for High Utility Pattern Mining Based on Top-k [PDF]

Jisuanji gongcheng, 2019
Getting the high utility pattern through user-specified threshold is inefficient,and the result of mining may not satisfy user’s needs.Therefore,an efficient Top-k pattern mining algorithm based on EFIM algorithm is proposed.The number of high utility ...
ZHAO Linliu,LV Xin,TAO Feifei
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

Mining Top-k High Average-Utility Sequential Patterns for Resource Transformation

Applied Sciences, 2023
High-utility sequential pattern mining (HUSPM) helps researchers find all subsequences that have high utility in a quantitative sequential database. The HUSPM approach appears to be well suited for resource transformation in DIKWP graphs.
Kai Cao, Yucong Duan
doaj   +1 more source

Mining high utility pattern with negative items in dynamic databases

International Journal of Intelligent Systems, 2021
High utility pattern mining with negative items (HUPMN) has more practical applications because it can process data with negative utility values. But the existing HUPMN algorithms assume that the database is static and it would be very expensive to use ...
M. Han, Ni Zhang, Le Wang, Xiaojuan Li, Haodong Cheng   +4 more
semanticscholar   +1 more source

Mining Correlated High Utility Itemsets in One Phase

IEEE Access, 2020
High-utility itemset mining (HUIM) in transaction databases has been extensively studied to discover interesting itemsets from users' purchase behaviors. With this, business managers can adjust their sale strategies appropriately to increase profit. HUIM
Bay Vo, Le V. Nguyen, Vinh V. Vu, Mi T. H. Lam, Thuy T. M. Duong, Ly T. Manh, Thuy T. T. Nguyen, Loan T. T. Nguyen, Tzung-Pei Hong   +8 more
doaj   +1 more source

Mining Significant Utility Discriminative Patterns in Quantitative Databases

Mathematics, 2023
Drawing a discriminative pattern in quantitative datasets is often represented to return a high utility pattern (HUP). The traditional methods output patterns with a utility above a pre-given threshold.
Huijun Tang, Jufeng Wang, Le Wang
doaj   +1 more source

Efficient Method for Mining High Utility Occupancy Patterns Based on Indexed List Structure

IEEE Access, 2023
High utility pattern mining has been proposed to improve the traditional support-based pattern mining methods that process binary databases. High utility patterns are discovered by effectively considering the quantity and importance of items.
Hyeonmo Kim, Taewoong Ryu, Chanhee Lee, Sinyoung Kim, Bay Vo, Jerry Chun-Wei Lin, Unil Yun   +6 more
doaj   +1 more source