Per Year

@article{hypercubeske-ia17,
   author = {Sabbatini, Federico and Ciatto, Giovanni and Calegari, Roberta and Omicini, Andrea},
   dblp = {journals/ia/SabbatiniCCO23},
   doi = {10.3233/IA-230001},
   editor = {Ferrando, Angelo and Mascardi, Viviana},
   iris = {11585/941033},
   journal = {Intelligenza Artificiale},
   keywords = {explainable AI, knowledge extraction, interpretable prediction, PSyKE},
   month = jun,
   note = {Special issue: Selected papers from the 23rd Workshop ``From Objects to Agents'' (WOA 2022)},
   number = 1,
   numpages = 13,
   pages = {63--75},
   publisher = {IOS Press},
   scholar = {14669296704428238758},
   scopus = {2-s2.0-85168332389},
   semanticscholar = {259324728},
   title = {Towards a Unified Model for Symbolic Knowledge Extraction with Hypercube-Based Methods},
   url = {https://content.iospress.com/articles/intelligenza-artificiale/ia230001},
   urlopenaccess = {https://cris.unibo.it/retrieve/3a2a510e-9dc5-4b07-b3f7-398cf2f21419/ia-2023-psyke.pdf},
   volume = 17,
   year = 2023
}

@article{psyke-ia16,
   author = {Sabbatini, Federico and Ciatto, Giovanni and Calegari, Roberta and Omicini, Andrea},
   dblp = {journals/ia/SabbatiniCCO22},
   doi = {10.3233/IA-210120},
   editor = {Calegari, Roberta and Ciatto, Giovanni and Omicini, Andrea and Vizzari, Giuseppe},
   eissn = {2211-0097},
   iris = {11585/890822},
   issn = {1724-8035},
   journal = {Intelligenza Artificiale},
   keywords = {Explainable AI, knowledge extraction, interpretable prediction, PSyKE},
   month = jul,
   number = 1,
   numpages = 22,
   pages = {27--48},
   publisher = {IOS Press},
   scholar = {7559675640918015038},
   scopus = {2-s2.0-85134193338},
   semanticscholar = {250400188},
   title = {Symbolic knowledge extraction from opaque {ML} predictors in {PSyKE}: Platform design \& experiments},
   url = {https://content.iospress.com/articles/intelligenza-artificiale/ia220141},
   volume = 16,
   wos = {WOS:000825367300003},
   year = 2022
}

@inproceedings{skemetrics-xaifin2022,
   address = {New York, NY, USA},
   author = {Sabbatini, Federico and Calegari, Roberta},
   booktitle = {Workshop on Explainable AI in Finance @ICAIF 2022},
   doi = {10.48550/arXiv.2211.00238},
   keywords = {Explainable artificial intelligence; Symbolic knowledge extraction; Readability metrics; AutoML},
   month = {November 2},
   scholar = {5021962022669458541},
   semanticscholar = {253244189},
   title = {Evaluation Metrics for Symbolic Knowledge Extracted from Machine Learning Black Boxes: A Discussion Paper},
   url = {https://arxiv.org/abs/2211.00238},
   urlopenaccess = {https://arxiv.org/abs/2211.00238},
   year = 2022
}

@incollection{hypercube-woa2022,
   author = {Sabbatini, Federico and Ciatto, Giovanni and Calegari, Roberta and Omicini, Andrea},
   booktitle = {WOA 2022 -- 23rd Workshop ``From Objects to Agents''},
   dblp = {conf/woa/SabbatiniCCO22},
   editor = {Ferrando, Angelo and Mascardi, Viviana},
   iris = {11585/899358},
   issn = {1613-0073},
   keywords = {Explainable AI; Knowledge extraction; Interpretable prediction; PSyKE},
   month = nov,
   numpages = 13,
   pages = {48--60},
   publisher = {Sun SITE Central Europe, RWTH Aachen University},
   scholar = {8614662013642803891},
   scopus = {2-s2.0-85142519111},
   semanticscholar = {253270041},
   series = {CEUR Workshop Proceedings},
   subseries = {AIxIA Series},
   title = {Hypercube-Based Methods for Symbolic Knowledge Extraction: Towards a Unified Model},
   url = {http://ceur-ws.org/Vol-3261/paper4.pdf},
   urlopenaccess = {http://ceur-ws.org/Vol-3261/paper4.pdf},
   urlpdf = {http://ceur-ws.org/Vol-3261/paper4.pdf},
   volume = 3261,
   year = 2022
}