Extending inverse frequent itemsets mining to generate realistic datasets: complexity, accuracy and emerging applications. Saccà, D., Serra, E., & Rullo, A. Data Min. Knowl. Discov., 33(6):1736–1774, 2019.
Extending inverse frequent itemsets mining to generate realistic datasets: complexity, accuracy and emerging applications [link]Paper  doi  bibtex   
@article{DBLP:journals/datamine/SaccaSR19,
  author       = {Domenico Sacc{\`{a}} and
                  Edoardo Serra and
                  Antonino Rullo},
  title        = {Extending inverse frequent itemsets mining to generate realistic datasets:
                  complexity, accuracy and emerging applications},
  journal      = {Data Min. Knowl. Discov.},
  volume       = {33},
  number       = {6},
  pages        = {1736--1774},
  year         = {2019},
  url          = {https://doi.org/10.1007/s10618-019-00643-1},
  doi          = {10.1007/S10618-019-00643-1},
  timestamp    = {Mon, 26 Oct 2020 00:00:00 +0100},
  biburl       = {https://dblp.org/rec/journals/datamine/SaccaSR19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

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