Back to Search
Start Over
Efficient algorithms for mining up-to-date high-utility patterns.
- Source :
-
Advanced Engineering Informatics . Aug2015, Vol. 29 Issue 3, p648-661. 14p. - Publication Year :
- 2015
-
Abstract
- High-utility pattern mining (HUPM) is an emerging topic in recent years instead of association-rule mining to discover more interesting and useful information for decision making. Many algorithms have been developed to find high-utility patterns (HUPs) from quantitative databases without considering timestamp of patterns, especially in recent intervals. A pattern may not be a HUP in an entire database but may be a HUP in recent intervals. In this paper, a new concept namely up-to-date high-utility pattern (UDHUP) is designed. It considers not only utility measure but also timestamp factor to discover the recent HUPs. The UDHUP-apriori is first proposed to mine UDHUPs in a level-wise way. Since UDHUP-apriori uses Apriori-like approach to recursively derive UDHUPs, a second UDHUP-list algorithm is then presented to efficiently discover UDHUPs based on the developed UDU-list structures and a pruning strategy without candidate generation, thus speeding up the mining process. A flexible minimum-length strategy with two specific lifetimes is also designed to find more efficient UDHUPs based on a users’ specification. Experiments are conducted to evaluate the performance of the proposed two algorithms in terms of execution time, memory consumption, and number of generated UDHUPs in several real-world and synthetic datasets. [ABSTRACT FROM AUTHOR]
- Subjects :
- *ASSOCIATION rule mining
*DECISION making
*TIMESTAMPS
*A priori
*DATA mining
Subjects
Details
- Language :
- English
- ISSN :
- 14740346
- Volume :
- 29
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Advanced Engineering Informatics
- Publication Type :
- Academic Journal
- Accession number :
- 109089705
- Full Text :
- https://doi.org/10.1016/j.aei.2015.06.002