Big Data Analytics in Association Rule Mining: A Systematic Literature Review
Mahtab Shahin, Sijo Arakkal Peious, Rahul Sharma, Minakshi Kaushik, Sadok Ben Yahia, Syed Attique Shah, Dirk Draheim
Abstract
Due to the rapid impact of IT technology, data across the globe is growing exponentially as compared to the last decade. Therefore, the efficient analysis and application of big data require special technologies. The present study performs a systematic literature review to synthesize recent research on the applicability of big data analytics in association rule mining (ARM). Our research strategy identified 4797 scientific articles, 27 of which were identified as primary papers relevant to our research. We have extracted data from these papers to identify various technologies and algorithms of using big data in association rule mining and identified their limitations in regards to the big data categories (volume, velocity, variety, and veracity).