[HTML][HTML] Incremental high average-utility itemset mining: survey and challenges
J Chen, S Yang, W Ding, P Li, A Liu, H Zhang, T Li - Scientific Reports, 2024 - nature.com
Abstract The High Average Utility Itemset Mining (HAUIM) technique, a variation of High
Utility Itemset Mining (HUIM), uses the average utility of the itemsets. Historically, most …
Utility Itemset Mining (HUIM), uses the average utility of the itemsets. Historically, most …
Efficient approach of high average utility pattern mining with indexed list-based structure in dynamic environments
H Kim, H Kim, M Cho, B Vo, JCW Lin, H Fujita… - Information Sciences, 2024 - Elsevier
Various studies on high utility pattern mining have been conducted to satisfy the emerging
need to consider the characteristics of real-world databases, such as the importance and …
need to consider the characteristics of real-world databases, such as the importance and …
Parallel approaches to extract multi-level high utility itemsets from hierarchical transaction databases
TDD Nguyen, NT Tung, T Pham, LTT Nguyen - Knowledge-Based Systems, 2023 - Elsevier
In the field of data mining, high utility itemset mining (HUIM) is a relevant mining task, with
the aim of analyzing customer transaction databases. HUIM consists of exploiting the set of …
the aim of analyzing customer transaction databases. HUIM consists of exploiting the set of …
MLC-miner: Efficiently discovering multi-level closed high utility patterns from quantitative hierarchical transaction databases
TDD Nguyen, NT Tung, LTT Nguyen, TT Pham… - Expert Systems with …, 2024 - Elsevier
High utility pattern mining (HUPM) extends frequent pattern mining (FPM) by including item
significance and quantity, which determine their utility, in transaction databases. A pattern is …
significance and quantity, which determine their utility, in transaction databases. A pattern is …
Advanced incremental erasable pattern mining from the time-sensitive data stream
H Kim, M Cho, H Nam, Y Baek, S Park, D Kim… - Knowledge-Based …, 2024 - Elsevier
Pattern mining has been actively advanced and studied in order to process data that is
generated in real time, called incremental data. Erasable pattern mining is a concept that …
generated in real time, called incremental data. Erasable pattern mining is a concept that …
Mining Interesting Sequential Patterns using a Novel Balanced Utility Measure
High utility sequential pattern (HUSP) mining (HUSM) is an emerging task in data mining.
The goal is to identify sequential patterns in a quantitative sequence database that have …
The goal is to identify sequential patterns in a quantitative sequence database that have …
RNP-Miner: Repetitive nonoverlapping sequential pattern mining
M Geng, Y Wu, Y Li, J Liu… - … on Knowledge and …, 2023 - ieeexplore.ieee.org
Sequential pattern mining (SPM) is an important branch of knowledge discovery that aims to
mine frequent sub-sequences (patterns) in a sequential database. Various SPM methods …
mine frequent sub-sequences (patterns) in a sequential database. Various SPM methods …
Incremental Top-k High Utility Pattern Mining and Analyzing over the Entire Accumulated Dynamic Database
C Lee, H Kim, M Cho, H Kim, B Vo, JCW Lin… - IEEE …, 2024 - ieeexplore.ieee.org
Top-k high utility pattern mining, which extracts the highest top-k patterns that the users want
to find, has been actively studied. Most previous studies in this domain have focused on …
to find, has been actively studied. Most previous studies in this domain have focused on …
Incremental mining algorithms for generating and updating frequent patterns for dynamic databases against insert, update, and support changes
S Borra, RR Rao - International Journal of Data Science and Analytics, 2024 - Springer
Developing algorithms for scalable and efficient itemset mining for large incremental
databases is paramount. When there is a significant change in the database or a threshold …
databases is paramount. When there is a significant change in the database or a threshold …
Repetitive nonoverlapping sequential pattern mining
M Geng, Y Wu, Y Li, J Liu, P Fournier-Viger… - arXiv preprint arXiv …, 2023 - arxiv.org
Sequential pattern mining (SPM) is an important branch of knowledge discovery that aims to
mine frequent sub-sequences (patterns) in a sequential database. Various SPM methods …
mine frequent sub-sequences (patterns) in a sequential database. Various SPM methods …