Results 31 to 40 of about 2,164 (156)

A log mining approach for process monitoring in SCADA [PDF]

, 2012
SCADA (Supervisory Control and Data Acquisition) systems are used for controlling and monitoring industrial processes. We propose a methodology to systematically identify potential process-related threats in SCADA. Process-related threats take place when
Bolzoni, Damiano, Hadziosmanovic, Dina, Hartel, Pieter   +2 more
core   +4 more sources

Generic Itemset Mining Based on Reinforcement Learning

IEEE Access, 2022
One of the biggest problems in itemset mining is the requirement of developing a data structure or algorithm, every time a user wants to extract a different type of itemsets.
Kazuma Fujioka, Kimiaki Shirahama
doaj   +1 more source

A Robust Technique for Closed Frequent and High Utility Itemsets Mining: Closed-FHUIM

IEEE Access
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, M. Asif Naeem, Heejeong Jasmine Lee   +2 more
doaj   +1 more source

HI-Tree: Mining High Influence Patterns Using External and Internal Utility Values [PDF]

, 2015
We propose an efficient algorithm, called HI-Tree, for mining high influence patterns for an incremental dataset. In traditional pattern mining, one would find the complete set of patterns and then apply a post-pruning step to it.
C Ahmed, CKS Leung, CW Lin, GC Lan, H Yao, J Han, SK Tanbeer, Y Liu   +7 more
core   +1 more source

Parallel Mining Algorithm for the Enumeration Space of Closed High Utility Itemsets

Journal of Harbin University of Science and Technology
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

Privacy Preserving Utility Mining: A Survey

, 2018
In big data era, the collected data usually contains rich information and hidden knowledge. Utility-oriented pattern mining and analytics have shown a powerful ability to explore these ubiquitous data, which may be collected from various fields and ...
Chao, Han-Chieh, Gan, Wensheng, Lin, Jerry Chun-Wei, Wang, Shyue-Liang, Yu, Philip S.   +4 more
core   +1 more source

Mining Frequent Graph Patterns with Differential Privacy [PDF]

, 2013
Discovering frequent graph patterns in a graph database offers valuable information in a variety of applications. However, if the graph dataset contains sensitive data of individuals such as mobile phone-call graphs and web-click graphs, releasing ...
Geweke J., Gilks W., Karwa V., Rubinstein R., Williams O., Yan X.   +5 more
core   +1 more source

Towards trajectory anonymization: a generalization-based approach [PDF]

, 2009
Trajectory datasets are becoming popular due to the massive usage of GPS and locationbased services. In this paper, we address privacy issues regarding the identification of individuals in static trajectory datasets.
Atzori, Maurizio, Guc, Baris, Güç, Barış, Nergiz, Mehmet Ercan, Saygin, Yucel, Saygın, Yücel   +5 more
core   +2 more sources

An Efficient Approach for Mining High Average-Utility Itemsets in Incremental Database

Engineering Proceedings
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, Chen-Chang Wu, Hsiang-En Kuo   +2 more
doaj   +1 more source

Incrementally Updating the Discovered High Average-Utility Patterns With the Pre-Large Concept

IEEE Access, 2020
High average-utility itemset mining (HAUIM) is an extension of high-utility itemset mining (HUIM), which provides a reliable measure to reveal utility patterns by considering the length of the mined pattern.
Jimmy Ming-Tai Wu, Qian Teng, Jerry Chun-Wei Lin, Chien-Fu Cheng   +3 more
doaj   +1 more source