IMBHN

This repository provides a reference implementation (Python) of the Inductive Model Based on Bipartite Heterogeneous Network (IMBHN) algorithm as described in [1]. [1] applies this algorithm to text classification and [2] adapts it to the word sense disambiguation scenario.

The code follows the scikit-learn framework, making it consistent with the scikit-learn APIs.

References

Please cite [1] and [2] if using this code.

[1] Rafael Geraldeli Rossi, Alneu de Andrade Lopes, Thiago de Paulo Faleiros, Solange Oliveira Rezende, Inductive model generation for text classification using a bipartite heterogeneous network

[2] Edilson A. Corrêa Jr, Alneu de A. Lopes, Diego R. Amancio, Word sense disambiguation: A complex network approach

@article{rossi2014inductive,
  title={Inductive model generation for text classification using a bipartite heterogeneous network},
  author={Rossi, Rafael Geraldeli and de Andrade Lopes, Alneu and de Paulo Faleiros, Thiago and Rezende, Solange Oliveira},
  journal={Journal of Computer Science and Technology},
  volume={29},
  number={3},
  pages={361--375},
  year={2014},
  publisher={Springer}
}

@article{correa2018word,
  title={Word sense disambiguation: a complex network approach},
  author={Corr{\^e}a, Edilson A and Lopes, Alneu A and Amancio, Diego R},
  journal={Information Sciences},
  year={2018},
  publisher={Elsevier}
}

For more information, you can contact me via edilsonacjr@gmail.com or edilsonacjr@usp.br.

Best, Edilson A. Corrêa Jr.