Results 71 to 80 of about 15,313,957 (171)
Modified GUIDE (LM) algorithm for mining maximal high utility patterns from data streams [PDF]
International Journal of Computational Intelligence Systems, 2015 High utility pattern mining is an emerging research topic in the data mining field. Unlike frequent pattern mining, high utility pattern mining deals with non-binary databases, in which the information about purchased quantities of items is maintained ...
Chiranjeevi Manike, Hari Om
doaj +1 more source
Journal of Advanced Transportation, Volume 2026, Issue 1, 2026.The purpose of this study was to explore the risk factors for autonomous vehicle (AV) crashes and their interdependencies. A total of 659 AV crash data were collected between 2018 and July 2024 from AV crash reports published by the California Department of Motor Vehicles.
Tao Wang +4 more
wiley +1 more source
Complexity, Volume 2026, Issue 1, 2026.Frequent itemset mining (FIM) is a fundamental task in data mining with applications ranging from market basket analysis and recommendation systems to fraud detection and bioinformatics. However, mining frequent itemsets from massive datasets remains computationally challenging due to high execution time and memory consumption.
Rahat Ali Shah +7 more
wiley +1 more source
Mining High Average-Utility Itemsets
, 2012 [[abstract]]The 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
Hong, Tzung-Pei; Lee, Cho-Han; Wang, Shyue-Liang
core
MINING CONCISE REPRESENTATIONS OF FREQUENT HIGH-UTILITY OCCUPANCY ITEMSETS USING GENERATOR PATTERNS
Tạp chí Khoa học Đại học Đà LạtA current trend in data mining is the discovery of frequent high-utility occupancy itemsets (FHUOIs) in quantitative databases. These itemsets capture user preferences and significantly contribute to transaction utility, making them valuable for real ...
Van Hai Duong +2 more
doaj +1 more source
Selective Database Projections Based Approach for Mining High-Utility Itemsets
IEEE Access, 2018 High-utility itemset mining (HilIM) is an emerging area of data mining and is widely used. HilIM differs from the frequent itemset mining (FIM), as the latter considers only the frequency factor, whereas the former has been designed to address both ...
Anita Bai +2 more
doaj +1 more source
Health &Social Care in the Community, Volume 2026, Issue 1, 2026.Background Middle‐aged and older adults with severe mental illness (SMI) often experience a higher burden of multiple chronic conditions compared with the general population. Despite this, limited research has explored how these conditions cluster and interact, particularly in social settings where integrated mental and physical healthcare remains ...
Yue-Hui Yu, Ya-Xuan Mao, Quan Lu
wiley +1 more source
Actionable high-coherent-utility fuzzy itemset mining
, 2016 Many fuzzy data mining approaches have been proposed for finding fuzzy association rules with the predefined minimum support from quantitative transaction databases.
Chen, C. H.;Li, A. F.;Lee, Y. C. +1 more
core +1 more source
Tạp chí Khoa học Đại học Đà Lạt, 2020 High Utility Itemset (HUI) mining is an important problem in the data mining literature that considers the utilities for businesses of items (such as profits and margins) that are discovered from transactional databases.
Cao Tùng Anh +2 more
doaj +1 more source
Identifying the Focus Word in Natural Language Questions Based on Association Rules
International Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.Knowledge base‐based intelligent question‐answering systems have insufficient understanding of the questions. In the early stages of research, it is effective in most cases that the existing natural language question‐understanding methods can answer questions by connecting entities and relationships when ignoring the identification of focus words ...
Xin Hu +5 more
wiley +1 more source