Results 41 to 50 of about 2,316 (204)

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

MEMU: More Efficient Algorithm to Mine High Average-Utility Patterns With Multiple Minimum Average-Utility Thresholds

IEEE Access, 2018
High average-utility itemsets mining (HAUIM) is an emerging topic in data mining. Compared to traditional high utility itemset mining, HAUIM more fairly measures the utility of itemsets by considering their lengths (number of items).
Jerry Chun-Wei Lin, Shifeng Ren, Philippe Fournier-Viger   +2 more
doaj   +1 more source

Algorithms Based on Dynamic Minimum Probabilistic Support and Utility Thresholds for Mining Top-K High-Utility Itemsets From Uncertain Databases

IEEE Access
Mining high-utility itemsets (HUIs) from large and uncertain databases is challenging due to the vast data volume and extensive search space. Determining the minimum utility and probabilistic support for all items is also a time-consuming task.
Khoi Nguyen, Thien Nguyen
doaj   +1 more source

FCHUIM: Efficient Frequent and Closed High-Utility Itemsets Mining

IEEE Access, 2020
Mining a closed high-utility itemset is a prevalent research task in analyzing transaction databases. However, numerous target itemsets are generated in the closed high-utility itemset mining task.
Tianyou Wei, Bin Wang, Yuntian Zhang, Keyong Hu, Yinfeng Yao, Hao Liu   +5 more
doaj   +1 more source

A One-Phase Tree-Structure Method to Mine High Temporal Fuzzy Utility Itemsets

Applied Sciences, 2022
Compared to fuzzy utility itemset mining (FUIM), temporal fuzzy utility itemset mining (TFUIM) has been proposed and paid attention to in recent years.
Tzung-Pei Hong, Cheng-Yu Lin, Wei-Ming Huang, Shu-Min Li, Shyue-Liang Wang, Jerry Chun-Wei Lin   +5 more
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

Developing and Validating an Instrument for Assessing Secondary Students' Self‐Efficacy for Online Reading

Reading Research Quarterly, Volume 61, Issue 2, April/May/June 2026.
This study introduces and validates the Self‐Efficacy for Online Reading Questionnaire (SEORQ), a process‐grounded instrument designed to measure secondary students' efficacy in executing the core demands of online reading. The model conceptualizes online reading self‐efficacy as a multidimensional construct encompassing five interrelated processes ...
SeongYeup Kim, Yongjun Lee, Elena Forzani   +2 more
wiley   +1 more source

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

Utility-driven Data Analytics on Uncertain Data

, 2019
Modern Internet of Things (IoT) applications generate massive amounts of data, much of it in the form of objects/items of readings, events, and log entries.
Chao, Han-Chieh, Gan, Wensheng, Lin, Jerry Chun-Wei, Vasilakos, Athanasios V., Yu, Philip S.   +4 more
core   +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