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Multi-Sorted Inverse Frequent Itemsets Mining
[article]
2013
arXiv
pre-print
The development of novel platforms and techniques for emerging "Big Data" applications requires the availability of real-life datasets for data-driven experiments, which are however out of reach for academic research in most cases as they are typically proprietary. A possible solution is to use synthesized datasets that reflect patterns of real ones in order to ensure high quality experimental findings. A first step in this direction is to use inverse mining techniques such as inverse frequent
arXiv:1310.3939v1
fatcat:aj54nykpfzakbkenmpl63fx3fy