Publications

Journal article on SINr, in-depth presentation and evaluation (preferred citation for method & python library)

  • Thibault Prouteau, Nicolas Dugué, Simon Guillot. From Communities to Interpretable Network and Word Embedding: an Unified Approach. Journal of Complex Networks, 2024, 12 (6), (10.1093/comnet/cnae034). ⟨hal-04829653⟩

Initial SINr paper, 2021

  • Thibault Prouteau, Victor Connes, Nicolas Dugué, Anthony Perez, Jean-Charles Lamirel, et al.. SINr: Fast Computing of Sparse Interpretable Node Representations is not a Sin!. Advances in Intelligent Data Analysis XIX, 19th International Symposium on Intelligent Data Analysis, IDA 2021, Apr 2021, Porto, Portugal. pp.325-337, ⟨10.1007/978-3-030-74251-5_26⟩. ⟨hal-03197434⟩

Interpretability of SINr embedding

  • Thibault Prouteau, Nicolas Dugué, Nathalie Camelin, Sylvain Meignier. Are Embedding Spaces Interpretable? Results of an Intrusion Detection Evaluation on a Large French Corpus. LREC 2022, Jun 2022, Marseille, France. ⟨hal-03770444⟩

Sparsity of SINr embedding

  • Simon Guillot, Thibault Prouteau, Nicolas Dugué. Sparser is better: one step closer to word embedding interpretability. IWCS 2023, Nancy, France. ⟨hal-04321407⟩

Filtering dimensions of SINr embedding

  • Anna Béranger, Nicolas Dugué, Simon Guillot, Thibault Prouteau. Filtering communities in word co-occurrence networks to foster the emergence of meaning. Complex Networks 2023, Menton, France. ⟨hal-04398742v1⟩

SINr library

  • Thibault Prouteau, Nicolas Dugué, Simon Guillot, Anthony Perez. SINr: a python package to train interpretable word and graph embeddings. French Regional Conference on Complex Systems, May 2023, Le Havre, France. pp.215, ⟨10.5281/zenodo.7957531⟩ <https://dx.doi.org/10.5281/zenodo.7957531>. ⟨hal-04113024⟩