Real-time stream data mining based on CanTree and Gtree-Reference-Cited by-同舟云学术

Real-time stream data mining based on CanTree and Gtree

Published:2016-11 Issue: Volume:367-368 Page:512-528
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Kim Jaein,Hwang Buhyun

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference43 articles.

1. Mining association rules between sets of items in large databases;Agrawal,1993

2. Real-Time motion trajectory-based indexing and retrieval of video sequences;Bashir;IEEE Trans. Multimed.,2007

3. Mining frequent itemsets in a stream;Calders;Inf. Syst.,2014

4. A dliding window method for finding recently frequent itemsets over online data streams;Chang;J. Inf. Sci. Eng.,2004

5. estWin: Online data stream mining of recent frequent itemsets by sliding window method;Chang;J. Inf. Sci.,2005

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A fast Apriori algorithm for telecom fraud;Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023);2023-10-17

2. A novel parallel frequent itemset mining algorithm for automatic enterprise;Enterprise Information Systems;2023-05-03

3. An instant discovery method for companion vehicles based on incremental and parallel calculation;Physica A: Statistical Mechanics and its Applications;2023-01

4. LCTree-Based Approach for Mining Frequent Items in Real-Time;Computational Intelligence and Neuroscience;2022-10-14

5. An Evolutive Frequent Pattern Tree-based Incremental Knowledge Discovery Algorithm;ACM Transactions on Management Information Systems;2022-02-04