TRICE: Mining Frequent Itemsets by Iterative TRimmed Transaction LattICE in Sparse Big Data

TRICE: Mining Frequent Itemsets by Iterative TRimmed Transaction LattICE in Sparse Big Data

Sparseness is often witnessed in big data emanating from a variety of sources, including IoT, pervasive computing, and behavioral data. Frequent itemset mining is the first and foremost step of association rule mining, which is a distinguished unsupervised machine learning problem. However, techniqu...

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Bibliographic Details
Main Authors: Muhammad Yasir, Muhammad Asif Habib, Muhammad Ashraf, Shahzad Sarwar, Muhammad Umar Chaudhry, Hamayoun Shahwani, Mudassar Ahmad, Ch. Muhammad Nadeem Faisal
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Association rules
big data applications
data mining
frequent itemset mining
pattern recognition
pervasive computing
Online Access:https://ieeexplore.ieee.org/document/8933017/

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