Tecnologie per l’analisi linguistica

L’attività di ricerca condotta da Daniele Radicioni si colloca nell'ambito dell'elaborazione automatica del linguaggio naturale. Negli ultimi anni si è prevalentemente concentrata sulla semantica lessicale, la rappresentazione della conoscenza, lo sviluppo di risorse per l'analisi lessicale e semantica del linguaggio, e su algoritmi per l'analisi di sequenze. Altre aree rilevanti sono le ontologie formali, gli spazi concettuali, le architetture cognitive e i modelli cognitivamente plausibili. Ha contribuito allo sviluppo di diverse risorse per la semantica lessicale e di dataset per la sperimentazione su specifici task.

 

 

Referenti

Daniele Radicioni (Dipartimento di Informatica)

 

 

Pubblicazioni

Davide Colla, Enrico Mensa, Daniele P. Radicioni. “LESSLEX: Linking Multilingual Embeddings to SenSe Representations of LEXical Items”. In:  Computational Linguistics, vol. 46, n. 2, 2020, pp. 289–333, 2020.

 

Davide Colla, Enrico Mensa, Daniele P. Radicioni. “Novel metrics for computing semantic similarity with sense embeddings”. In: Knowledge-Based Systems, 206:106346, 2020.

 

Davide Colla, Enrico Mensa, Daniele P. Radicioni. “Sense identification data: a dataset for lexical semantics”. In: Data in Brief, 32:106267, 2020.

 

Francesca Garbarini, Fabrizio Calzavarini, Matteo Diano, Monica Biggio, Carola Barbero, Daniele P. Radicioni, Giuliano Geminiani, Katiuscia Sacco, Diego Marconi. “Imageability effect on the functional brain activity during a naming to definition task”. In: Neuropsychologia, 137:107275, 2020.

 

Annamaria Goy, Davide Colla, Diego Magro, Cristina Accornero, Fabrizio Loreto, Daniele P. Radicioni. “Building semantic metadata for historical archives through an ontology-driven user interface”. In: ACM Journal on Computing and Cultural Heritage, vol. 13, n. 3, 2020, pp. 1-36.

 

Lorenzo Gregori, Maria Montefinese, Daniele P. Radicioni, Andrea Amelio Ravelli, Rossella Varvara. “CONcreTEXT @ EVALITA2020: the Concreteness in Context Task”. In: Valerio Basile, Danilo Croce, Maria Di Maro, and Lucia C. Passaro, editors, Proceedings of the 7th Evaluation Campaign of Natural Language Processing and Speech tools for Italian (EVALITA 2020), Online, CEUR, 2020.

 

Enrico Mensa, Davide Colla, Marco Dalmasso, Marco Giustini, Carlo Mamo, Alessio Pitidis, Daniele P. Radicioni. “Violence detection explanation via semantic roles embeddings”. In: BMC Medical Informatics and Decision Making, vol. 20, n. 1, 2020, pp. 263–275.

 

Enrico Mensa, Gian Manuel Marino, Davide Colla, Matteo Delsanto, Daniele P. Radicioni. “A Resource for Detecting Misspellings and Denoising Medical Text Data”. In: Felice Dell’Orletta, Johanna Monti, and Fabio Tamburini, editors, Proceedings of the Seventh Italian Conference on Computational Linguistics (CLiC-it 2020). Online, CEUR, 2020.

 

Valerio Basile, Tommaso Caselli, Daniele P. Radicioni. “Meaning in Context: Ontologically and linguistically motivated representations of objects and events”. In: Applied Ontology, 2019, n. 14, pp. 335–341.

 

Giulio Carducci, Marco Leontino, Daniele P. Radicioni, Guido Bonino, Enrico Pasini, Paolo Tripodi. “Semantically Aware Text Categorisation for Metadata Annotation”. In: P. Manghi, L. Candela, G. Silvello, editors, Digital Libraries: Supporting Open Science. IRCDL 2019. Communications in Computer and Information Science, vol. 988, Chams, Springer, 2019. https://doi.org/10.1007/978-3-030-11226-4_25

 

Davide Colla, Marco Leontino, Enrico Mensa, Daniele P. Radicioni. “From Sartre to Frege in Three Steps: A Search for Enriching Semantic Text Similarity Measures”. In: Proceedings of the Sixth Italian Conference on Computational Linguistics, Bari, November 13-15, 2019.

 

Annamaria Goy, Cristina Accornero, Dunia Astrologo, Davide Colla, Matteo D’Ambrosio, Rossana Damiano, Marco Leontino, Antonio Lieto, Fabrizio Loreto, Diego Magro, Enrico Mensa, Alice Montanaro, Valeria Mosca, Stefano Musso, Daniele P. Radicioni, Cristina Re. “Fruitful synergies between computer science, historical studies and archives: The experience in the PRISMHA project”. In: Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2019, Volume 3: KMIS, Vienna, Austria, September 17-19, 2019, pp. 225–230.

 

Aureliano Porporato, Alessandro Mazzei, Daniele P. Radicioni, Rosa Meo. “Evaluating the MuMe dialogue system with the IDIAL protocol”. In: Proceedings of the Sixth Italian Conference on Computational Linguistics, Bari, November 13-15, 2019, 2019.

 

Davide Colla, Enrico Mensa, Aureliano Porporato, Daniele P. Radicioni. “Conceptual Abstractness: From Nouns to Verbs”. In: Proceedings of the Fifth Italian Conference on Computational Linguistics (CLiC-it 2018), volume 2253. CEUR, 2018.

 

Davide Colla, Enrico Mensa, Daniele P. Radicioni, Antonio Lieto. “Tell Me Why: Computational Explanation of Conceptual Similarity Judgments”. In: J. Medina et al., editors, Proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), Special Session on Advances on Explainable Artificial Intelligence, volume 853 of Communications in Computer and Information Science (CCIS), Cham, Springer International Publishing, 2018, pp. 74–84.

 

Enrico Mensa, Aureliano Porporato, Daniele P. Radicioni. “Annotating concept abstractness by common-sense knowledge”. In: Chiara Ghidini, Bernardo Magnini, Andrea Passerini, Paolo Traverso, editors, AI*IA 2018 – Advances in Artificial Intelligence, Cham, Springer International Publishing, 2018, pp. 415–428.

 

Enrico Mensa, Aureliano Porporato, Daniele P. Radicioni. “Grasping metaphors: Lexical semantics in metaphor analysis”. In: Aldo Gangemi, Anna Lisa Gentile, Andrea Giovanni Nuzzolese, Sebastian Rudolph, Maria Maleshkova, Heiko Paulheim, Jeff Z Pan, Mehwish Alam, editors, The Semantic Web: ESWC 2018 Satellite Events, Cham, Springer International Publishing, 2018, pp. 192–195.

 

Enrico Mensa, Daniele P. Radicioni, Antonio Lieto. “COVER: a linguistic resource combining common sense and lexicographic information”. In: Language Resources and Evaluation, vol. 52, n. 4, 2018, pp. 921–948.