Looking for a structural characterization of the sparseness measure of (frequent closed) itemset contexts-Reference-Cited by-同舟云学术

Looking for a structural characterization of the sparseness measure of (frequent closed) itemset contexts

Published:2013-02 Issue: Volume:222 Page:343-361
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Hamrouni T.,Ben Yahia S.,Mephu Nguifo E.

Publisher

Elsevier BV

Subject

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

Reference68 articles.

1. An effective and efficient algorithm for high-dimensional outlier detection;Aggarwal;International Journal on Very Large Data Bases,2005

2. Fast discovery of association rules;Agrawal,1996

3. Redundant association rules reduction techniques;Ashrafi;International Journal of Business Intelligence and Data Mining,2007

4. An algorithm to mine general association rules from tabular data;Ayubi;Information Sciences,2009

5. Mining frequent closed unordered trees through natural representations;Balcázar,2007

Cited by 13 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 assessment of formal concept stability in the Galois lattice;International Journal of General Systems;2022-07-31

2. Introducing the closure structure and the GDPM algorithm for mining and understanding a tabular dataset;International Journal of Approximate Reasoning;2022-06

3. Interval association of remote sensing ecological index in China based on concept lattice;Environmental Science and Pollution Research;2022-01-16

4. Concept Lattice Method for Spatial Association Discovery in the Urban Service Industry;ISPRS International Journal of Geo-Information;2020-03-09

5. An insight into biological datamining based on rarity and correlation as constraints;Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing;2019-04-08