Multi-Sorted Inverse Frequent Itemsets Mining for Generating Realistic No-SQL Datasets (Discussion Paper)

Domenico SaccĂ , Edoardo Serra, Antonino Rullo. Multi-Sorted Inverse Frequent Itemsets Mining for Generating Realistic No-SQL Datasets (Discussion Paper). In Sergio Greco, Maurizio Lenzerini, Elio Masciari, Andrea Tagarelli, editors, Proceedings of the 29th Italian Symposium on Advanced Database Systems, SEBD 2021, Pizzo Calabro (VV), Italy, September 5-9, 2021. Volume 2994 of CEUR Workshop Proceedings, pages 347-354, CEUR-WS.org, 2021. [doi]

@inproceedings{SaccaSR21,
  title = {Multi-Sorted Inverse Frequent Itemsets Mining for Generating Realistic No-SQL Datasets (Discussion Paper)},
  author = {Domenico SaccĂ  and Edoardo Serra and Antonino Rullo},
  year = {2021},
  url = {http://ceur-ws.org/Vol-2994/paper38.pdf},
  researchr = {https://researchr.org/publication/SaccaSR21},
  cites = {0},
  citedby = {0},
  pages = {347-354},
  booktitle = {Proceedings of the 29th Italian Symposium on Advanced Database Systems, SEBD 2021, Pizzo Calabro (VV), Italy, September 5-9, 2021},
  editor = {Sergio Greco and Maurizio Lenzerini and Elio Masciari and Andrea Tagarelli},
  volume = {2994},
  series = {CEUR Workshop Proceedings},
  publisher = {CEUR-WS.org},
}