A quick algorithm for incremental mining closed frequent itemsets over data streams-Reference-Cited by-同舟云学术

A quick algorithm for incremental mining closed frequent itemsets over data streams

Published:2015 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Second ACM IKDD Conference on Data Sciences - CoDS '15
language:
Short-container-title:

Author:

Naik Shankar B.,Pawar Jyoti D.

Publisher

ACM Press

Reference8 articles.

1. Agrawal, R. and Shrikant, R. 1994. Fast algorithms for mining association rules.Proceedings of the 20thinternational conference on very large databases, 487--499, (1994).

2. Babock, B., Babu, S., Motwani, R. and Widom. J. 2002 Models and issues in data stream systems.Proceedings of the 21stACM SIGMOD-SIGACT-AIGART symposium on principles of database systems, 1--16, (2002).

3. Chang, J., and Lee, W.(2004) Decaying obsolete information in finding recent frequent itemsets over data stream.IEICE Transaction on Informations and Systems, 6, (2004).

4. Chang, J., and Lee, W. 2004. A sliding window method for finding recently frequent itemsets over online data streams.Journal of information science and engineering, 4, (2004).

5. Chi Y., Wang, H., Yu, P., and Muntz. R. 2004. MOMENT: Maintaining closed frequent itemsets over a stream sliding window,Proceedings of the 4thIEEE international conference on data mining, 59--66, (2004).

Cited by 4 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. Efficient High Utility Itemset Mining Using Genetic Algorithms and Bit-Vector Optimization;Lecture Notes in Networks and Systems;2024

2. High Utility Itemset Mining Using Genetic Approach;Communications in Computer and Information Science;2022

3. Stable High Utility Itemset Mining;The 23rd International Conference on Information Integration and Web Intelligence;2021-11-29

4. Application of Association Rule Mining-Based Attribute Value Generation in Music Composition;Advances in Intelligent Systems and Computing;2021