Mining Periodic-Frequent Patterns in Irregular Dense Temporal Databases Using Set Complements-Reference-Cited by-同舟云学术

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Mining Periodic-Frequent Patterns in Irregular Dense Temporal Databases Using Set Complements

Published:2023 Issue: Volume:11 Page:118676-118688
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Veena Pamalla¹^ORCID,Sreepada Tarun²^ORCID,Kiran Rage Uday²^ORCID,Dao Minh-Son³^ORCID,Zettsu Koji³^ORCID,Watanobe Yutaka²^ORCID,Zhang Ji⁴

Affiliation:

1. Sri Balaji PG College, JNTU-Anantapur, Anantapur, Andhra Pradesh, India

2. Division of Information Systems, The University of Aizu, Aizuwakamatsu, Fukushima, Japan

3. National Institute of Information and Communications Technology, Koganei, Tokyo, Japan

4. School of Mathematics, Physics and Computing, the University of Southern Queensland, Toowoomba, QLD, Australia

Funder

Japan Society for the Promotion of Science (JSPS) KAKENHI

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10288493.pdf?arnumber=10288493

Reference43 articles.

1. Efficient Mining of Non-Redundant Periodic Frequent Patterns

2. Discovering Stable Periodic-Frequent Patterns in Transactional Data

3. Towards fast and memory efficient discovery of periodic frequent patterns

4. Discovering Fuzzy Periodic-Frequent Patterns in Quantitative Temporal Databases

5. H-Mine: Fast and space-preserving frequent pattern mining in large databases

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