Results 31 to 40 of about 15,313,957 (171)

IEEE Access Special Section Editorial: Utility-Pattern Mining: Theoretical Analytics and Applications

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, Philippe Fournier-Viger, Vincent S. Tseng, Philip S. Yu   +3 more
doaj   +1 more source

HIGH UTILITY ITEMSETS MINING

, 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
YING LIU, YONG SHI, JIANWEI LI, WEI-KENG LIAO, ALOK CHOUDHARY   +4 more
core   +1 more source

Fast Identification of High Utility Itemsets from Candidates [PDF]

, 2018
High utility itemsets (HUIs) are sets of items with high utility, like profit, in a database. Efficient mining of high utility itemsets is an important problem in the data mining area. Many mining algorithms adopt a two-phase framework.
Chunsheng Xin, Qu, Jun-Feng, Jun-Feng Qu, Mengchi Liu, Xin, Chunsheng, Liu, Mengchi, Zhongbo Wu, Wu, Zhongbo   +7 more
core   +1 more source

Algorithms Based on Dynamic Minimum Probabilistic Support and Utility Thresholds for Mining Top-K High-Utility Itemsets From Uncertain Databases

IEEE Access
Mining high-utility itemsets (HUIs) from large and uncertain databases is challenging due to the vast data volume and extensive search space. Determining the minimum utility and probabilistic support for all items is also a time-consuming task.
Khoi Nguyen, Thien Nguyen
doaj   +1 more source

MEMU: More Efficient Algorithm to Mine High Average-Utility Patterns With Multiple Minimum Average-Utility Thresholds

IEEE Access, 2018
High average-utility itemsets mining (HAUIM) is an emerging topic in data mining. Compared to traditional high utility itemset mining, HAUIM more fairly measures the utility of itemsets by considering their lengths (number of items).
Jerry Chun-Wei Lin, Shifeng Ren, Philippe Fournier-Viger   +2 more
doaj   +1 more source

FCHUIM: Efficient Frequent and Closed High-Utility Itemsets Mining

IEEE Access, 2020
Mining a closed high-utility itemset is a prevalent research task in analyzing transaction databases. However, numerous target itemsets are generated in the closed high-utility itemset mining task.
Tianyou Wei, Bin Wang, Yuntian Zhang, Keyong Hu, Yinfeng Yao, Hao Liu   +5 more
doaj   +1 more source

A One-Phase Tree-Structure Method to Mine High Temporal Fuzzy Utility Itemsets

Applied Sciences, 2022
Compared to fuzzy utility itemset mining (FUIM), temporal fuzzy utility itemset mining (TFUIM) has been proposed and paid attention to in recent years.
Tzung-Pei Hong, Cheng-Yu Lin, Wei-Ming Huang, Shu-Min Li, Shyue-Liang Wang, Jerry Chun-Wei Lin   +5 more
doaj   +1 more source

Association Rule Mining for Accidental Dwelling Fire Incidence Data Analysis in Greater Manchester, UK

Fire and Materials, EarlyView.
ABSTRACT Association rule mining was used to identify patterns in accidental dwelling fire incidents attended by Greater Manchester Fire and Rescue Service over the period 2013/14 to 2023/24. The association rule mining process identified relationships between cooking fire incidence, distraction, living alone, deprivation, and fire injury.
M. Taylor, R. Lyon, D. Doolan, E. Dean, J. Fielding, M. Thomas   +5 more
wiley   +1 more source

Generic Itemset Mining Based on Reinforcement Learning

IEEE Access, 2022
One of the biggest problems in itemset mining is the requirement of developing a data structure or algorithm, every time a user wants to extract a different type of itemsets.
Kazuma Fujioka, Kimiaki Shirahama
doaj   +1 more source

Efficient heuristics for the Steiner forest problem

International Transactions in Operational Research, EarlyView.
Abstract Let G=(V,E)$G = (V, E)$ be a connected undirected graph, V$V$ a set of nodes, E$E$ a set of edges, |V|=n$|V| = n$, and |E|=m$|E| = m$. Given a non‐negative weight function w:E→R+$w: E \rightarrow \mathbb {R}^+$ associated with its edges, a set τ={Ti⊆V|i=1,…,p}$\tau = \lbrace T_i \subseteq V | i = 1, \ldots, p\rbrace$ of terminal sets Ti$T_i ...
Murilo Stockinger, Isabel Rosseti, Simone Martins, Luidi Simonetti, Alexandre Plastino   +4 more
wiley   +1 more source