An Efficient Spark-Based Hybrid Frequent Itemset Mining Algorithm for Big Data
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DOI: 10.3390/data7010011
Abstract: Frequent itemset mining (FIM) is a common approach for discovering hidden frequent patterns from transactional databases used in prediction, association rules, classification, etc. Apriori is an FIM elementary algorithm with iterative nature used to find… read more here.
Keywords: spark; frequent itemset; itemset mining; spark based ... See more keywords
Big data clustering techniques based on Spark: a literature review
Sign Up to like & getrecommendations! Published in 2020 at "PeerJ Computer Science"
DOI: 10.7717/peerj-cs.321
Abstract: A popular unsupervised learning method, known as clustering, is extensively used in data mining, machine learning and pattern recognition. The procedure involves grouping of single and distinct points in a group in such a way… read more here.
Keywords: big data; spark; spark based; clustering methods ... See more keywords