Results 31 to 40 of about 15,313,538 (164)
A Robust Technique for Closed Frequent and High Utility Itemsets Mining: Closed-FHUIM
Frequent itemset mining (FIM) and high utility itemset mining (HUIM) are popular data mining techniques used in various real-world applications such as retail-market, bio-medicine, and click-stream analysis.
Muhammad Waheed Ashraf +2 more
doaj +1 more source
Improved Genetic Algorithm for High-Utility Itemset Mining
High-utility itemset mining (HUIM) is an important research topic in the data mining field. Typically, traditional HUIM algorithms must handle the exponential problem of huge search space when the database size or number of distinct items is very large ...
Qiang Zhang +3 more
doaj +1 more source
Itemset mining is an important subfield of data mining, which consists of discovering interesting and useful patterns in transaction databases. The traditional task of frequent itemset mining is to discover groups of items (itemsets) that appear ...
Jerry Chun‐Wei Lin +11 more
core +1 more source
An Efficient Approach for Mining High Average-Utility Itemsets in Incremental Database
Traditional high-utility itemset (HUI) mining methods tend to overestimate utility for long itemsets, leading to biased results. High average-utility itemset (HAUI) mining addresses this problem by normalizing utility with itemset length.
Ye-In Chang +2 more
doaj +1 more source
Parallel Mining Algorithm for the Enumeration Space of Closed High Utility Itemsets
To address the issues of result redundancy and time overhead in high-dimensional data environments, a closed high utility itemset mining algorithm, SpCHUIM (Closed High Utility Itemsets Mining on Spark), is proposed.
LI Chengyan, SUN Anqi, LIU Songlin
doaj +1 more source
An Evolutionary Algorithm to Mine High-Utility Itemsets
High-utility itemset mining (HUIM) is a critical issue in recent years since it can be used to reveal the profitable products by considering both the quantity and profit factors instead of frequent itemset mining (FIM) of association rules (ARs). In this
Jerry Chun-Wei Lin +5 more
doaj +1 more source
Proof Learning in PVS With Utility Pattern Mining
Interactive theorem provers (ITPs) are software tools that allow human users to write and verify formal proofs. In recent years, an emerging research area in ITPs is proof mining, which consists of identifying interesting proof patterns that can be used ...
M. Saqib Nawaz +2 more
doaj +1 more source
Pruning Strategy on Adaptive Rule Model by Sorting Utility Items
The adaptive Rule Model is an association rule development that formulates a minimum threshold value according to the data characteristics. The formulation process is based on item frequency and utility for other considerations, which requires high ...
Erna Hikmawati +2 more
doaj +1 more source
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 +5 more
wiley +1 more source
Closed High Utility Pattern Mining over Data Stream Based on Projection in the Window
A fast and effective algorithm EFIM_Closed_DS was proposed to mine closed and high utility itemsets in the data stream environment. The algorithm is based on the projection technology in the window, and the database projection technology and transaction ...
Muhang LI +4 more
doaj +1 more source

