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Link prediction techniques, applications, and performance: A survey
Link prediction finds missing links (in static networks) or predicts the likelihood of future links
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …
Efficient approach of sliding window-based high average-utility pattern mining with list structures
C Lee, T Ryu, H Kim, H Kim, B Vo, JCW Lin… - Knowledge-Based …, 2022 - Elsevier
Data mining has been actively studied, and it has become more important due to the
development of information technology and the demands of diverse applications, such as …
development of information technology and the demands of diverse applications, such as …
An efficient utility-list based high-utility itemset mining algorithm
Z Cheng, W Fang, W Shen, JCW Lin, B Yuan - Applied Intelligence, 2023 - Springer
High-utility itemset mining (HUIM) is an important task in data mining that can retrieve more
meaningful and useful patterns for decision-making. One-phase HUIM algorithms based on …
meaningful and useful patterns for decision-making. One-phase HUIM algorithms based on …
New approaches for mining regular high utility sequential patterns
Regular pattern mining has been emerged as one of the promising sub-domains of data
mining by discovering patterns with regular occurrences throughout a complete database. In …
mining by discovering patterns with regular occurrences throughout a complete database. In …
Efficient mining of cross-level high-utility itemsets in taxonomy quantitative databases
NT Tung, LTT Nguyen, TDD Nguyen, P Fourier-Viger… - Information …, 2022 - Elsevier
In contrast to frequent itemset mining (FIM) algorithms that focus on identifying itemsets with
high occurrence frequency, high-utility itemset mining algorithms can reveal the most …
high occurrence frequency, high-utility itemset mining algorithms can reveal the most …
Efficient high utility itemset mining without the join operation
Y Yan, X Niu, Z Zhang, P Fournier-Viger, L Ye, F Min - Information Sciences, 2024 - Elsevier
The task of mining high-utility itemsets in a database given a minimum threshold is attracting
more and more interest due to its many applications. Existing algorithms such as the vertical …
more and more interest due to its many applications. Existing algorithms such as the vertical …
UGMINE: utility-based graph mining
Frequent pattern mining extracts most frequent patterns from databases. These frequency-
based frameworks have limitations in representing users' interest in many cases. In business …
based frameworks have limitations in representing users' interest in many cases. In business …
TKN: an efficient approach for discovering top-k high utility itemsets with positive or negative profits
M Ashraf, T Abdelkader, S Rady, TF Gharib - Information Sciences, 2022 - Elsevier
Top-k high utility itemsets (HUIs) mining permits discovering the required number of patterns-
k, without having an optimal minimum utility threshold (ie, minimum profit). Multiple top-k …
k, without having an optimal minimum utility threshold (ie, minimum profit). Multiple top-k …
Ftkhuim: a fast and efficient method for mining top-k high-utility itemsets
High-utility itemset mining (HUIM) is an important task in the field of knowledge data
discovery. The large search space and huge number of HUIs are the consequences of …
discovery. The large search space and huge number of HUIs are the consequences of …
RHUPS: Mining recent high utility patterns with sliding window–based arrival time control over data streams
Databases that deal with the real world have various characteristics. New data is
continuously inserted over time without limiting the length of the database, and a variety of …
continuously inserted over time without limiting the length of the database, and a variety of …