EclatDS: An efficient sliding window based frequent pattern mining method for data streams
Author:
Affiliation:
1. Department of Computer Science and Engineering, School of Engineering, Shiraz University, Shiraz, Iran
Publisher
IOS Press
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Theoretical Computer Science
Cited by 19 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 Variable Sliding Window Algorithm Based on Concept Drift for Frequent Pattern Mining Over Data Streams*;2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS);2023-01
2. Efficient Probabilistic Frequent Closed Itemsets Mining for Uncertain Data;SSRN Electronic Journal;2022
3. An Automated Penetration Semantic Knowledge Mining Algorithm Based on Bayesian Inference;Computers, Materials & Continua;2021
4. A Sliding Window-Based Approach for Mining Frequent Weighted Patterns Over Data Streams;IEEE Access;2021
5. Multiclass Weighted Associative Classifier with Application-Based Rule Selection for Data Gathered Using Wireless Sensor Networks;Evolutionary Computing and Mobile Sustainable Networks;2020-08-01
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