Papers › Revisiting Distributional Correspondence Indexing: A Python Reimplementation and New...
Revisiting Distributional Correspondence Indexing: A Python Reimplementation and New Experiments
Alejandro Moreo, Andrea Esuli, Fabrizio Sebastiani
This paper introduces PyDCI, a new implementation of Distributional Correspondence Indexing (DCI) written in Python. DCI is a transfer learning method for cross-domain and cross-lingual text classification for which we had provided an implementation (here called JaDCI) built on top of JaTeCS, a Java framework for text classification. PyDCI is a stand-alone version of DCI that exploits scikit-learn and the SciPy stack. We here report on new experiments that we have carried out in order to test PyDCI, and in which we use as baselines new high-performing methods that have appeared after DCI was originally proposed. These experiments show that, thanks to a few subtle ways in which we have improved DCI, PyDCI outperforms both JaDCI and the above-mentioned high-performing methods, and delivers the best known results on the two popular benchmarks on which we had tested DCI, i.e., MultiDomainSentiment (a.k.a. MDS -- for cross-domain adaptation) and Webis-CLS-10 (for cross-lingual adaptation). PyDCI, together with the code allowing to replicate our experiments, is available at https://github.com/AlexMoreo/pydci .
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Sentiment Analysis | Multi-Domain Sentiment Dataset | Distributional Correspondence Indexing | Average | 83.30 | #2 of 6 | Archive leaderboard | report |
| Sentiment Analysis | Multi-Domain Sentiment Dataset | Distributional Correspondence Indexing | Books | 81.4 | #2 of 6 | Archive leaderboard | report |
| Sentiment Analysis | Multi-Domain Sentiment Dataset | Distributional Correspondence Indexing | DVD | 81.00 | #2 of 6 | Archive leaderboard | report |
| Sentiment Analysis | Multi-Domain Sentiment Dataset | Distributional Correspondence Indexing | Electronics | 85,06 | #2 of 6 | Archive leaderboard | report |
| Sentiment Analysis | Multi-Domain Sentiment Dataset | Distributional Correspondence Indexing | Kitchen | 85.9 | #2 of 6 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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