Results 61 to 70 of about 5,295 (219)
An AI knowledge‐based system for police assistance in crime investigation
Expert Systems, Volume 42, Issue 1, January 2025.Abstract The fight against crime is often an arduous task overall when huge amounts of data have to be inspected, as is currently the case when it comes for example in the detection of criminal activity on the dark web. This work presents and describes an artificial intelligence (AI) based system that combines various tools to assist police or law ...
Carlos Fernandez‐Basso +4 more
wiley +1 more source
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 +4 more
wiley +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
A Multi-Core Approach to Efficiently Mining High-Utility Itemsets in Dynamic Profit Databases
IEEE Access, 2020 Analyzing customer transactions to discover high-utility itemsets is a popular task, which consists of finding the sets of items that are purchased together and yield a high profit.
Bay Vo +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
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
Reconstructing thicket clump formation using association rules analysis
Journal of Vegetation Science, Volume 35, Issue 3, May/June 2024.Association rules (or market basket) analysis was effective in eliciting common associations between species and size classes across different stages of thicket clump formation in a savanna. Vachellia karroo established alone in open grassland, whereas a suite of clump‐initiating species recruited in close association with large V.
Rhys Nell +2 more
wiley +1 more source
DLLog: An Online Log Parsing Approach for Large‐Scale System
International Journal of Intelligent Systems, Volume 2024, Issue 1, 2024.Syslog is a critical data source for analyzing system problems. Converting unstructured log entries into structured log data is necessary for effective log analysis. However, existing log parsing methods demonstrate promising accuracy on limited datasets, but their generalizability and precision are uncertain when applied to diverse log data ...
Hailong Cheng +4 more
wiley +1 more source
A Model for Predicting IoT User Behavior Based on Bayesian Learning and Neural Networks
Journal of Computer Networks and Communications, Volume 2024, Issue 1, 2024.To facilitate the allocation of energy and resources in the Internet of Things system, this paper presents a model for predicting user behavior in Internet of Things environments. The model is based on Bayesian learning and neural networks and is designed to provide insights into the future behavior of users, allowing for the allocation of resources in
Xin Xu +3 more
wiley +1 more source
A Survey of High-utility Itemsets Mining
Journal of Physics: Conference Series, 2020 Abstract Data mining is of significance for finding useful information in massive data. Frequent itemsets mining (FIM ) and high-utility itemsets mining(HUIM) are extremely common and wide application in research and real life. For one thing, HUIM algorithm focuses on utility, which is more practical.
Haijun Yang, Yonghua Lu, Bolan Zhang
openaire +1 more source