Results 81 to 90 of about 45,837 (241)
Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance Guarantees [PDF]
, 2013 The tasks of extracting (top-$K$) Frequent Itemsets (FI's) and Association Rules (AR's) are fundamental primitives in data mining and database applications. Exact algorithms for these problems exist and are widely used, but their running time is hindered
Riondato, Matteo, Upfal, Eli
core
Unveiling Success Drivers in Gaming: A Machine Learning Study Across Steam, Twitch, and Metacritic
International Journal of Computer Games Technology, Volume 2025, Issue 1, 2025.This study employs machine learning to assess the relative impact of major platforms—Steam, Twitch, and Metacritic—on video game revenue. Through an integrated analysis of three comprehensive datasets comprising commercially successful titles on Steam, key predictors of financial performance were identified.
Jiesi Ma, Michael J. Katchabaw
wiley +1 more source
Theoretical Properties of Closed Frequent Itemsets in Frequent Pattern Mining
MathematicsClosed frequent itemsets (CFIs) play a crucial role in frequent pattern mining by providing a compact and complete representation of all frequent itemsets (FIs).
Huina Zhang +4 more
doaj +1 more source
An Improved Apriori Algorithm for Association Rules
, 2014 There are several mining algorithms of association rules. One of the most popular algorithms is Apriori that is used to extract frequent itemsets from large database and getting the association rule for discovering the knowledge. Based on this algorithm,
Al-Maolegi, Mohammed, Arkok, Bassam
core +1 more source
Data‐Driven Materials Research and Development for Functional Coatings
Advanced Science, Volume 11, Issue 42, November 13, 2024.Functional coatings play a vital role in various industries for their protective and functional properties. However, its design often involves time‐consuming experimentation with multiple materials and processing parameters. To overcome these limitations, data‐driven approaches are gaining traction in materials science. This review provides an overview
Kai Xu +8 more
wiley +1 more source
AN EFFICIENT ALGORITHM FOR MINING HIGH UTILITY ITEMSETS
Tạp chí Khoa họcHigh utility itemsets (HUIs) mining is the finding of itemsets that satisfy a user-defined minimum utility threshold. Many successful studies in this field have been carried out, however they are all reliant on Tidset techniques, which records the ...
Nguyen Thi Thanh Thuy*, Nguyen Van Le, Manh Thien Ly
doaj +1 more source
Constraint Programming for Mining Borders of Frequent Itemsets
International Joint Conference on Artificial Intelligence, 2019 Frequent itemset mining is one of the most studied tasks in knowledge discovery. It is often reduced to mining the positive border of frequent itemsets, i.e. maximal frequent itemsets.
M. Belaid, C. Bessiere, Nadjib Lazaar
semanticscholar +1 more source
IET Generation, Transmission &Distribution, Volume 18, Issue 13, Page 2313-2324, July 2024.This paper proposes an electric vehicle (EV) load diagnosis algorithm considering data privacy. The validity of the algorithm in this paper is verified by using the real collected EV load data. Abstract Accurate forecasting of electric vehicle (EV) load is essential for grid stability and energy management. EV load forecasting is influenced by multiple
Ruien Bian +3 more
wiley +1 more source
A Robust Technique for Closed Frequent and High Utility Itemsets Mining: Closed-FHUIM
IEEE AccessFrequent 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
An improvement of FP-Growth association rule mining algorithm based on adjacency table
MATEC Web of Conferences, 2018 FP-Growth algorithm is an association rule mining algorithm based on frequent pattern tree (FP-Tree), which doesn’t need to generate a large number of candidate sets.
Yin Ming +3 more
doaj +1 more source