Mining maximal frequent patterns in transactional databases and dynamic data streams: A spark-based approach
Work
Year: 2017
Type: article
Source: Information Sciences
Institutions RWTH Aachen University, Fraunhofer Institute for Applied Information Technology, University of Jyväskylä, University of Dhaka
Cites: 49
Cited by: 60
Related to: 10
FWCI: 17.13
Citation percentile (by year/subfield): 95.71
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Sustainable Development Goal Industry, innovation and infrastructure
Open Access status: closed