Incrementally Mining High Utility Itemsets in Dynamic Databases

2010 ◽  
Author(s):  
Chun-Wei Lin ◽  
Tzung-Pei Hong ◽  
Guo-Cheng Lan ◽  
Hsin-Yi Chen ◽  
Hung-Yu Kao
Keyword(s):  
Dynamic Databases ◽  
High Utility ◽  
High Utility Itemsets

Efficient updating of discovered high-utility itemsets for transaction deletion in dynamic databases

2015 ◽  
Vol 29 (1) ◽  
pp. 16-27 ◽  
Author(s):  
Chun-Wei Lin ◽  
Tzung-Pei Hong ◽  
Guo-Cheng Lan ◽  
Jia-Wei Wong ◽  
Wen-Yang Lin
Keyword(s):  
Dynamic Databases ◽  
High Utility ◽  
High Utility Itemsets

scholarly journals Dynamic maintenance model for high average-utility pattern mining with deletion operation

2021 ◽  
Author(s):  
Jimmy Ming-Tai Wu ◽  
Qian Teng ◽  
Shahab Tayeb ◽  
Jerry Chun-Wei Lin
Keyword(s):  
Pattern Mining ◽  
Computational Cost ◽  
Practical Applications ◽  
Itemset Mining ◽  
Dynamic Databases ◽  
Speed Up ◽  
Dynamic Maintenance ◽  
Average Utility ◽  
High Utility ◽  
Maintenance Model

AbstractThe high average-utility itemset mining (HAUIM) was established to provide a fair measure instead of genetic high-utility itemset mining (HUIM) for revealing the satisfied and interesting patterns. In practical applications, the database is dynamically changed when insertion/deletion operations are performed on databases. Several works were designed to handle the insertion process but fewer studies focused on processing the deletion process for knowledge maintenance. In this paper, we then develop a PRE-HAUI-DEL algorithm that utilizes the pre-large concept on HAUIM for handling transaction deletion in the dynamic databases. The pre-large concept is served as the buffer on HAUIM that reduces the number of database scans while the database is updated particularly in transaction deletion. Two upper-bound values are also established here to reduce the unpromising candidates early which can speed up the computational cost. From the experimental results, the designed PRE-HAUI-DEL algorithm is well performed compared to the Apriori-like model in terms of runtime, memory, and scalability in dynamic databases.

An efficient fast algorithm for discovering closed+ high utility itemsets

2016 ◽  
Vol 45 (1) ◽  
pp. 44-74 ◽  
Author(s):  
Jayakrushna Sahoo ◽  
Ashok Kumar Das ◽  
A. Goswami
Keyword(s):  
Fast Algorithm ◽  
High Utility ◽  
High Utility Itemsets

Efficient algorithms for mining closed high utility itemsets in dynamic profit databases

2021 ◽  
Vol 186 ◽  
pp. 115741
Author(s):  
Trinh D.D. Nguyen ◽  
Loan T.T. Nguyen ◽  
Lung Vu ◽  
Bay Vo ◽  
Witold Pedrycz
Keyword(s):  
Efficient Algorithms ◽  
High Utility ◽  
High Utility Itemsets

MINING CORRELATED HIGH UTILITY ITEMSETS ON INCREMENTAL DATABASE

2021 ◽  
Author(s):  
Nguyen Van Le ◽  
Nguyen Thi Thanh Thuy ◽  
Manh Thien Ly
Keyword(s):  
High Utility ◽  
High Utility Itemsets
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