OCEAN: Fast Discovery of High Utility Occupancy Itemsets-Reference-Cited by-同舟云学术

OCEAN: Fast Discovery of High Utility Occupancy Itemsets

Published:2016 Issue: Volume: Page:354-365
ISSN:0302-9743
Container-title:Advances in Knowledge Discovery and Data Mining
language:
Short-container-title:

Author:

Shen Bilong,Wen Zhaoduo,Zhao Ying,Zhou Dongliang,Zheng Weimin

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-31753-3_29

Reference15 articles.

1. Frequent itemset mining implementations repository. http://fimi.ua.ac.be/data/

2. Ahmed, C.F., Tanbeer, S.K., Jeong, B.S., Lee, Y.K.: Efficient tree structures for high utility pattern mining in incremental databases. IEEE Trans. Knowl. Data Eng. 21(12), 1708–1721 (2009)

3. Burdick, D., Calimlim, M., Gehrke, J.: Mafia: A maximal frequent itemset algorithm for transactional databases. In: Proceedings of the 17th International Conference on Data Engineering (ICDE), pp. 443–452. IEEE (2001)

4. Chan, R.C., Yang, Q., Shen, Y.D.: Mining high utility itemsets. In: Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM), pp. 19–26. IEEE (2003)

5. Lecture Notes in Computer Science;P Fournier-Viger,2014

Cited by 18 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 algorithms to mine concise representations of frequent high utility occupancy patterns;Applied Intelligence;2024-03

2. HAUOPM: High Average Utility Occupancy Pattern Mining;Arabian Journal for Science and Engineering;2023-06-21

3. Efficient Method for Mining High Utility Occupancy Patterns Based on Indexed List Structure;IEEE Access;2023

4. Comparison and Experimental Analysis of Information Interaction Models in Operation Simulation System;Lecture Notes in Electrical Engineering;2023

5. Pattern Discovery with Utility Occupancy;2022 IEEE International Conference on Big Data (Big Data);2022-12-17