Results 61 to 70 of about 311 (178)

An Efficient Algorithm for Mining Top-k High-On-Shelf-Utility Itemsets with Positive/Negative Profits of Local/Global Minimum Count

Engineering Proceedings
High-utility itemset mining (HUIM) utilizes the threshold value to extract HUI from the transactional database. However, it is difficult to define an optimal threshold value, since it depends on the domain knowledge of the application.
Ye-In Chang, Po-Chun Chuang, Yu-Hao Liao, Po-Yu Hu, Ting-Wei Chen   +4 more
doaj   +1 more source

Induction of Non-monotonic Logic Programs To Explain Statistical Learning Models [PDF]

Electronic Proceedings in Theoretical Computer Science, 2019
We present a fast and scalable algorithm to induce non-monotonic logic programs from statistical learning models. We reduce the problem of search for best clauses to instances of the High-Utility Itemset Mining (HUIM) problem.
Farhad Shakerin
doaj   +1 more source

Research on Risk Identification of Coal Mine Ventilation Systems Based on HFACS and Apriori Algorithm

Advances in Civil Engineering, Volume 2025, Issue 1, 2025.
The coal industry has always been a typically high‐risk industry with frequent accidents and extremely adverse impacts. Cases of accidents in coal mine ventilation systems serve as a concentrated demonstration of accident hazards and hold significant value for identifying key risk factors that may induce disasters in coal mine ventilation systems. This
Mingjia Jing, Guoxing Zhang, Dongjie Yang, Hongli Qin, Manoj Khandelwal   +4 more
wiley   +1 more source

PUC: parallel mining of high-utility itemsets with load balancing on spark

Journal of Intelligent Systems, 2022
Distributed programming paradigms such as MapReduce and Spark have alleviated sequential bottleneck while mining of massive transaction databases. Of significant importance is mining High Utility Itemset (HUI) that incorporates the revenue of the items ...
Brahmavar Anup Bhat, Sheeranalli Venkatarama Harish, Maiya Geetha   +2 more
doaj   +1 more source

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

Enhancing Interpretability: A Hierarchical Belief Rule‐Based (HBRB) Method for Assessing Multimodal Social Media Credibility

International Journal of Intelligent Systems, Volume 2025, Issue 1, 2025.
User and artificial intelligence generated contents, coupled with the multimodal nature of information, have made the identification of false news an arduous task. While models can assist users in improving their cognitive abilities, commonly used black‐box models lack transparency, posing a significant challenge for interpretability.
Peng Wu, Jiahong Lin, Zhiyuan Ma, Huiwen Li, Mohammad Rezwan Habib   +4 more
wiley   +1 more source

Psychosocial factors associated with physical activity in people with dementia: A pilot cross‐sectional study

AGING MEDICINE, Volume 7, Issue 5, Page 543-552, October 2024.
Factors significantly associated with physical activity outcomes in people with dementia in the final regression models. The figure highlights that psychosocial factors are associated with different constructs related to physical activity. Only the presence of intrapersonal barriers to physical activity was associated with both total physical activity ...
Nicolas Farina, Uzma Niazi, Riona Mc Ardle, Johanna Eronen, Ruth Lowry, Sube Banerjee   +5 more
wiley   +1 more source

Electric vehicle load forecasting based on convolutional networks with attention mechanism and federated learning method

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, Long Wang, Yadong Liu, Zhou Dai   +3 more
wiley   +1 more source

Frequent Closed High-Utility Itemset Mining Algorithm Based on Leiden Community Detection and Compact Genetic Algorithm

IEEE Access
Traditional pattern mining algorithms are based on tree and linked list structures. However, they often only consider a single factor of frequency or utility and have to deal with exponential search spaces as well as generate numerous candidates.
Xiumei Zhao, Xincheng Zhong, Bing Han
doaj   +1 more source

Mining High Utility Itemsets with Regular Occurrence

Journal of ICT Research and Applications, 2016
High utility itemset mining (HUIM) plays an important role in the data mining community and in a wide range of applications. For example, in retail business it is used for finding sets of sold products that give high profit, low cost, etc. These itemsets
Komate Amphawan, Philippe Lenca, Anuchit Jitpattanakul, Athasit Surarerks   +3 more
doaj   +1 more source