Results 71 to 80 of about 2,164 (156)
Mining high utility sequential patterns [PDF]
, 2015 University of Technology Sydney. Faculty of Engineering and Information Technology.Sequential pattern mining refers to the identification of frequent subsequences in sequence databases as patterns.
Yin, J
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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
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
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
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 +3 more
doaj +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
Selective Database Projections Based Approach for Mining High-Utility Itemsets
IEEE Access, 2018 High-utility itemset mining (HilIM) is an emerging area of data mining and is widely used. HilIM differs from the frequent itemset mining (FIM), as the latter considers only the frequency factor, whereas the former has been designed to address both ...
Anita Bai +2 more
doaj +1 more source
A Framework for High-Accuracy Privacy-Preserving Mining
, 2004 To preserve client privacy in the data mining process, a variety of techniques based on random perturbation of data records have been proposed recently.
Agrawal, Shipra, Haritsa, Jayant R.
core +3 more sources
Using association rule mining to enrich semantic concepts for video retrieval [PDF]
, 2009 In order to achieve true content-based information retrieval on video we should analyse and index video with high-level semantic concepts in addition to using user-generated tags and structured metadata like title, date, etc.
Fatemi, Nastaran +3 more
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