Extracting sequential frequent itemsets from probabilistic sequences database-Reference-Cited by-同舟云学术

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Extracting sequential frequent itemsets from probabilistic sequences database

Published:2023-05-23 Issue:5 Volume:15 Page:2509-2515
ISSN:2511-2104
Container-title:International Journal of Information Technology
language:en
Short-container-title:Int. j. inf. tecnol.

Author:

Seddiki Imane,Nouioua Farid,Barkat Abdelbasset^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s41870-023-01292-w.pdf

Reference18 articles.

1. Agrawal R, Imieliński T, Swami A. Mining association rules between sets of items in large databases. In: Proceedings of the 1993 ACM SIGMOD international conference on Management of data 1993, p. 207–216

2. Gupta MK, Chandra P (2020) A comprehensive survey of data mining. Int J Informat Technol 12(4):1243–1257

3. Jiang Fan, Leung Carson K, Sarumi Oluwafemi A, Zhang Christine Y (2016) Mining sequential patterns from uncertain big DNA in the spark framework. In: 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, pp 874–881

4. Sekhar SM, Siddesh GM, Raj M, Manvi SS (2021) Protein class prediction based on Count Vectorizer and long short term memory. Int J Informat Technol 13(1):341–348

5. Zhao Z, Yan D, Ng W (2013) Mining probabilistically frequent sequential patterns in large uncertain databases. IEEE Trans Knowled Data Eng 26(5):1171–84

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