Lightweight and Scalable Model for Tweet Engagements Predictions in a Resource-constrained Environment. Carminati, L., Lodigiani, G., Maldini, P., Meta, S., Metaj, S., Pisa, A., Sanvito, A., Surricchio, M., Maurera, F. B. P., Bernardis, C., & Ferrari Dacrema, M. In RecSys Challenge 2021: Proceedings of the Recommender Systems Challenge 2021, Amsterdam, The Netherlands, 1 October 2021, pages 28–33, 2021. ACM.
Lightweight and Scalable Model for Tweet Engagements Predictions in a Resource-constrained Environment [link]Paper  doi  bibtex   
@inproceedings{DBLP:conf/recsys/CarminatiLMMMPS21,
  author       = {Luca Carminati and
                  Giacomo Lodigiani and
                  Pietro Maldini and
                  Samuele Meta and
                  Stiven Metaj and
                  Arcangelo Pisa and
                  Alessandro Sanvito and
                  Mattia Surricchio and
                  Fernando Benjam{\'{\i}}n P{\'{e}}rez Maurera and
                  Cesare Bernardis and
                  Maurizio {Ferrari Dacrema}},
  title        = {Lightweight and Scalable Model for Tweet Engagements Predictions in
                  a Resource-constrained Environment},
  booktitle    = {RecSys Challenge 2021: Proceedings of the Recommender Systems Challenge
                  2021, Amsterdam, The Netherlands, 1 October 2021},
  pages        = {28--33},
  publisher    = {{ACM}},
  year         = {2021},
  url          = {https://doi.org/10.1145/3487572.3487597},
  doi          = {10.1145/3487572.3487597},
  timestamp    = {Sun, 02 Oct 2022 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/conf/recsys/CarminatiLMMMPS21.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

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