A highly scalable parallel algorithm for maximally informative k-itemset mining-Reference-Cited by-同舟云学术

A highly scalable parallel algorithm for maximally informative k-itemset mining

Published:2016-03-22 Issue:1 Volume:50 Page:1-26
ISSN:0219-1377
Container-title:Knowledge and Information Systems
language:en
Short-container-title:Knowl Inf Syst

Author:

Salah Saber,Akbarinia Reza,Masseglia Florent

Funder

Hemera

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Hardware and Architecture,Human-Computer Interaction,Information Systems,Software

Link

http://link.springer.com/content/pdf/10.1007/s10115-016-0931-2.pdf

Reference34 articles.

1. Agrawal R, Srikant R (1994) Fast algorithms for mining association rules in large databases. In: Proceedings of international conference on very large data bases (VLDB), pp 487–499

2. Amazon (n.d.) , http://snap.stanford.edu/data/web-Amazon-links.html

3. Anand R (2012) Mining of massive datasets. Cambridge University Press, New York

4. Berberich K, Bedathur S (2013) Computing n-gram statistics in mapreduce. In: Proceedings of the 16th international conference on extending database technology (EDBT), pp 101–112

5. Berry M (2008) Survey of text mining II clustering, classification, and retrieval. Springer, New York

Cited by 8 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. HMA-ID mechanism: a hybrid mayfly optimisation based apriori approach for intrusion detection in big data application;Telecommunication Systems;2022-03-10

2. Mining predicate rules without minimum support threshold;Kuwait Journal of Science;2021-08-17

3. Map-optimize-reduce: CAN tree assisted FP-growth algorithm for clusters based FP mining on Hadoop;Future Generation Computer Systems;2020-02

4. A review on big data based parallel and distributed approaches of pattern mining;Journal of King Saud University - Computer and Information Sciences;2019-09

5. A Survey of Parallel Sequential Pattern Mining;ACM Transactions on Knowledge Discovery from Data;2019-07-17