SoftId: An autoencoder-based one-class classification model for software authorship identification

Mihaiela Lupea, Anamaria Briciu, István Gergely Czibula, Gabriela Czibula. SoftId: An autoencoder-based one-class classification model for software authorship identification. In Matteo Cristani, Carlos Toro 0001, Cecilia Zanni-Merk, Robert J. Howlett, Lakhmi C. Jain, editors, Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 26th International Conference KES-2022, Verona, Italy and Virtual Event, 7-9 September 2022. Volume 207 of Procedia Computer Science, pages 716-725, Elsevier, 2022. [doi]

@inproceedings{LupeaBCC22,
  title = {SoftId: An autoencoder-based one-class classification model for software authorship identification},
  author = {Mihaiela Lupea and Anamaria Briciu and István Gergely Czibula and Gabriela Czibula},
  year = {2022},
  doi = {10.1016/j.procs.2022.09.127},
  url = {https://doi.org/10.1016/j.procs.2022.09.127},
  researchr = {https://researchr.org/publication/LupeaBCC22},
  cites = {0},
  citedby = {0},
  pages = {716-725},
  booktitle = {Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 26th International Conference KES-2022, Verona, Italy and Virtual Event, 7-9 September 2022},
  editor = {Matteo Cristani and Carlos Toro 0001 and Cecilia Zanni-Merk and Robert J. Howlett and Lakhmi C. Jain},
  volume = {207},
  series = {Procedia Computer Science},
  publisher = {Elsevier},
}