Our publications

This is the list of the publications related to our resources.

D. Colla, E. Mensa, and D. P. Radicioni, “Sense identification data: a dataset for lexical semantics,” Data in brief, vol. 32, p. 106267, 2020.
[Bibtex]

@article{colla2020sense,
title={Sense identification data: A dataset for lexical semantics},
author={Colla, Davide and Mensa, Enrico and Radicioni, Daniele P},
journal={Data in Brief},
year={2020},
volume={32},
pages={106267},
publisher={Elsevier},
pdf={https://www.sciencedirect.com/science/article/pii/S2352340920311616}
}

D. Colla, E. Mensa, and D. P. Radicioni, “Lesslex: linking multilingual embeddings to sense representations of lexical items,” Computational linguistics, vol. 46, iss. 2, pp. 289-333, 2020.
[Bibtex]

@article{colla2020lesslex,
author = {Colla, Davide and Mensa, Enrico and Radicioni, Daniele P.},
title = {LessLex: Linking Multilingual Embeddings to SenSe Representations of LEXical Items},
journal = {Computational Linguistics},
volume = {46},
number = {2},
pages = {289-333},
year = {2020},
doi = {10.1162/coli\_a\_00375},
URL = {
https://doi.org/10.1162/coli_a_00375
},
eprint = {
https://doi.org/10.1162/coli_a_00375
}
,
abstract = { We present LESSLEX, a novel multilingual lexical resource. Different from the vast majority of existing approaches, we ground our embeddings on a sense inventory made available from the BabelNet semantic network. In this setting, multilingual access is governed by the mapping of terms onto their underlying sense descriptions, such that all vectors co-exist in the same semantic space. As a result, for each term we have thus the “blended” terminological vector along with those describing all senses associated to that term. LESSLEX has been tested on three tasks relevant to lexical semantics: conceptual similarity, contextual similarity, and semantic text similarity. We experimented over the principal data sets for such tasks in their multilingual and crosslingual variants, improving on or closely approaching state-of-the-art results. We conclude by arguing that LESSLEX vectors may be relevant for practical applications and for research on conceptual and lexical access and competence. },
pdf={http://www.mitpressjournals.org/doi/pdf/10.1162/COLI_a_00375}
}

F. Garbarini, F. Calzavarini, M. Diano, M. Biggio, C. Barbero, D. P. Radicioni, G. Geminiani, K. Sacco, and D. Marconi, “Imageability effect on the functional brain activity during a naming to definition task,” Neuropsychologia, vol. 137, p. 107275, 2020.
[Bibtex]

@article{garbarini2020imageability,
title={Imageability effect on the functional brain activity during a naming to definition task},
author={Garbarini, Francesca and Calzavarini, Fabrizio and Diano, Matteo and Biggio, Monica and Barbero, Carola and Radicioni, Daniele P and Geminiani, Giuliano and Sacco, Katiuscia and Marconi, Diego},
journal={Neuropsychologia},
volume={137},
pages={107275},
year={2020},
publisher={Elsevier},
pdf={https://iris.unito.it/retrieve/handle/2318/1725799/572524/Imageability.pdf}
}

D. Colla, E. Mensa, and D. P. Radicioni, “Novel metrics for computing semantic similarity with sense embeddings,” Knowledge-based systems, vol. 206, p. 106346, 2020.
[Bibtex]

@article{colla2020novel,
title={Novel metrics for computing semantic similarity with sense embeddings},
author={Colla, Davide and Mensa, Enrico and Radicioni, Daniele P},
journal={Knowledge-Based Systems},
year={2020},
volume={206},
pages={106346},
publisher={Elsevier},
pdf={https://www.sciencedirect.com/science/article/pii/S0950705120305025}
}

G. Carducci, M. Leontino, D. P. Radicioni, G. Bonino, E. Pasini, and P. Tripodi, “Semantically aware text categorisation for metadata annotation,” in Italian research conference on digital libraries, 2019, p. 315–330.
[Bibtex]

@inproceedings{carducci2019semantically,
title={Semantically aware text categorisation for metadata annotation},
author={Carducci, Giulio and Leontino, Marco and Radicioni, Daniele P and Bonino, Guido and Pasini, Enrico and Tripodi, Paolo},
booktitle={Italian Research Conference on Digital Libraries},
pages={315--330},
year={2019},
organization={Springer},
pdf={https://iris.unito.it/retrieve/handle/2318/1693870/483956/carducci2019categorization.pdf}
}

D. Colla, M. Leontino, E. Mensa, and D. P. Radicioni, “From sartre to frege in three steps: a* search for enriching semantic text similarity measures,” in Sixth italian conference on computational linguistics, 2019, p. 131–138.
[Bibtex]

@inproceedings{colla2019sartre,
title={From Sartre to Frege in three steps: A* search for enriching semantic text similarity measures},
author={Colla, Davide and Leontino, Marco and Mensa, Enrico and Radicioni, Daniele P},
booktitle={Sixth Italian Conference on Computational Linguistics},
pages={131--138},
year={2019},
organization={CEUR},
pdf={https://iris.unito.it/retrieve/handle/2318/1724233/567997/colla2019sartre.pdf}
}

V. Basile, C. Tommaso, D. P. Radicioni, and others, “Meaning in context: ontologically and linguistically motivated representations of objects and events,” , 2019.
[Bibtex]

@article{basile2019meaning,
title={Meaning in Context: Ontologically and linguistically motivated representations of objects and events},
author={Basile, Valerio and Tommaso, Caselli and Radicioni, Daniele P and others},
year={2019},
pdf={https://iris.unito.it/retrieve/handle/2318/1724262/568067/basile2019meaning_preprint.pdf}
}

E. Mensa, D. P. Radicioni, and A. Lieto, “COVER: a linguistic resource combining common sense and lexicographic information,” Language Resources and Evaluation, vol. 52, iss. 4, p. 921–948, 2018.
[Bibtex]

@article{mensa2018cover,
author={Mensa, Enrico
and Radicioni, Daniele P.
and Lieto, Antonio},
title={{COVER: a linguistic resource combining common sense and lexicographic information}},
journal={{Language Resources and Evaluation}},
year={2018},
month={Dec},
day={01},
volume={52},
number={4},
pages={921--948},
abstract={Lexical resources are fundamental to tackle many tasks that are central to present and prospective research in Text Mining, Information Retrieval, and connected to Natural Language Processing. In this article we introduce COVER, a novel lexical resource, along with COVERAGE, the algorithm devised to build it. In order to describe concepts, COVER proposes a compact vectorial representation that combines the lexicographic precision characterizing BabelNet and the rich common-sense knowledge featuring ConceptNet. We propose COVER as a reliable and mature resource, that has been employed in as diverse tasks as conceptual categorization, keywords extraction, and conceptual similarity. The experimental assessment is performed on the last task: we report and discuss the obtained results, pointing out future improvements. We conclude that COVER can be directly exploited to build applications, and coupled with existing resources, as well.},
issn={1574-0218},
doi={10.1007/s10579-018-9417-z},
url={https://doi.org/10.1007/s10579-018-9417-z},
pdf={https://rdcu.be/1qFJ}
}

“Grasping metaphors: lexical semantics in metaphor analysis,” in The Semantic Web: ESWC 2018 Satellite Events, Cham, 2018, p. 192–195.
[Bibtex]

@inproceedings{mensa18grasping,
editor={Gangemi, Aldo
and Gentile, Anna Lisa
and Nuzzolese, Andrea Giovanni
and Rudolph, Sebastian
and Maleshkova, Maria
and Paulheim, Heiko
and Pan, Jeff Z
and Alam, Mehwish},
title={Grasping Metaphors: Lexical Semantics in Metaphor Analysis},
booktitle= {{The Semantic Web: ESWC 2018 Satellite Events}},
year={2018},
publisher={Springer International Publishing},
address={Cham},
pages={192--195},
abstract={Metaphors represent to date an extraordinary challenge for computational linguistics. Dealing with metaphors has relevant consequences on our ability to build agents and systems that understand Natural Language and text documents: annotating metaphoric constructions by linking the metaphor elements to existing resources is a crucial step to make text documents more easily accessible by machines. Our approach tackles metaphors by considering concepts and their abstractness. We report the encouraging results obtained in a preliminary experimentation; we elaborate on present limitations, and individuate the needed improvements, which will be the base for future work.},
isbn={978-3-319-98192-5},
pdf = {http://delorean.di.unito.it/ls/papers/mensa18grasping.pdf}
}

E. Mensa, A. Porporato, and D. P. Radicioni, “Annotating Concept Abstractness by Common-sense Knowledge,” in Proceedings of the 17th International Conference of the Italian Association for Artificial Intelligence, Trento, 2018.
[Bibtex]

@inproceedings{mensa2018annotating,
Address = {Trento},
Author = {Mensa, Enrico and Porporato, Aureliano and Radicioni, Daniele P.},
Booktitle = {{Proceedings of the 17th International Conference of the Italian Association for Artificial Intelligence}},
Publisher = {Springer International Publishing},
Year= {2018},
Series = {Lecture Notes in Artificial Intelligence (LNAI)},
Title = {{Annotating Concept Abstractness by Common-sense Knowledge}},
pdf={https://iris.unito.it/retrieve/handle/2318/1685415/462642/mensa2018annotating.pdf}
}

D. Colla, E. Mensa, D. P. Radicioni, and A. Lieto, “Tell me why: computational explanation of conceptual similarity judgments,” in 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, Cham, 2018, p. 74–85.
[Bibtex]

@inproceedings{colla2018tell,
Abstract = {In this paper we introduce a system for the computation of explanations that accompany scores in the conceptual similarity task. In this setting the problem is, given a pair of concepts, to provide a score that expresses in how far the two concepts are similar. In order to explain how explanations are automatically built, we illustrate some basic features of \CVR, the lexical resource that underlies our approach, and the main traits of the \MERALI system, that computes conceptual similarity and explanations, all in one. To assess the computed explanations, we have designed a human experimentation, that provided interesting and encouraging results, which we report and discuss in depth.},
Address = {Cham},
Author = {Colla, Davide and Mensa, Enrico and Radicioni, Daniele P. and Lieto, Antonio},
Booktitle = {{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}},
Publisher = {Springer International Publishing},
Editor = {J. Medina et al.},
Series = {Communications in Computer and Information Science (CCIS)},
Volume = {853},
Pages = {74--85},
Title = {Tell Me Why: Computational Explanation of Conceptual Similarity Judgments},
Url = {https://doi.org/10.1007/978-3-319-91473-2_7},
Year = {2018},
pdf={http://www.di.unito.it/~radicion/papers/colla2018tell.pdf}
}

D. Colla, E. Mensa, A. Porporato, and D. P. Radicioni, “Conceptual Abstractness: from Nouns to Verbs,” in Proceedings of the Fifth Italian Conference on Computational Linguistics (CLIC-IT 2018), 2018, to appear.
[Bibtex]

@inproceedings{colla2018conceptual,
Author = {Colla, Davide and Mensa, Enrico and Porporato, Aureliano and Radicioni, Daniele P.},
Booktitle = {{Proceedings of the Fifth Italian Conference on Computational Linguistics (CLIC-IT 2018)}},
Year= {2018, to appear},
Title = {{Conceptual Abstractness: from Nouns to Verbs}},
pdf={https://pdfs.semanticscholar.org/aa37/0d7283622f31cb94a6a40ab2b69a93670567.pdf?_ga=2.140391923.1352130253.1583421779-504358248.1583421779}
}

E. Mensa, D. P. Radicioni, and A. Lieto, “TTCS^e: a Vectorial Resource for Computing Conceptual Similarity,” in Proceedings of the 1st Workshop on Sense, Concept and Entity Representations and their Applications, Valencia, Spain, 2017, p. 96–101.
[Bibtex]

@InProceedings{mensa17ttcse,
author = {Mensa, Enrico and Radicioni, Daniele P. and Lieto, Antonio},
title = {{TTCS^e: a Vectorial Resource for Computing Conceptual Similarity}},
booktitle = {{Proceedings of the 1st Workshop on Sense, Concept and Entity Representations and their Applications}},
month = {April},
year = {2017},
address = {Valencia, Spain},
publisher = {Association for Computational Linguistics},
pages = {96--101},
abstract = {In this paper we introduce the TTCS\^{}e, a linguistic resource that relies on
BabelNet, NASARI and ConceptNet, that has now been used to compute the
conceptual similarity between concept pairs. The conceptual representation
herein provides uniform access to concepts based on BabelNet synset IDs, and
consists of a vector-based semantic representation which is compliant with the
Conceptual Spaces, a geometric framework for common-sense knowledge
representation and reasoning. The TTCS\^{}e has been evaluated in a preliminary
experimentation on a conceptual similarity task.},
url = {http://www.aclweb.org/anthology/W17-1912},
pdf = {http://delorean.di.unito.it/ls/papers/mensa17ttcse.pdf}
}

E. Mensa, D. P. Radicioni, and A. Lieto, “MERALI at SemEval-2017 Task 2 Subtask 1: a Cognitively Inspired approach,” in Proceedings of the International Workshop on Semantic Evaluation (SemEval 2017), 2017.
[Bibtex]

@InProceedings{mensa17merali,
author = {Mensa, Enrico and Radicioni, Daniele P. and Lieto, Antonio},
title = {{MERALI at SemEval-2017 Task 2 Subtask 1: a Cognitively Inspired approach}},
booktitle={{Proceedings of the International Workshop on Semantic Evaluation (SemEval 2017)}},
year = {2017},
publisher = {{Association for Computational Linguistics}},
abstract = {In this paper we report on the participation of the MeRaLi system to the SemEval Task 2 Subtask 1. The MeRaLi system approaches conceptual similarity through a simple, cognitively inspired, heuristics; it builds on a linguistic resource, the TTCSe, that relies on BabelNet, NASARI and ConceptNet. The linguistic resource in fact contains a novel mixture of common-sense and encyclopedic knowledge. The obtained results point out that there is ample room for improvement, so that they are used to elaborate on present limitations and on future steps.},
pdf = {http://delorean.di.unito.it/ls/papers/mensa17merali.pdf}
}

A. Lieto, D. P. Radicioni, V. Rho, and E. Mensa, “Towards a Unifying Framework for Conceptual Represention and Reasoning in Cognitive Systems,” Intelligenza Artificiale, vol. 11, iss. 2, pp. 139-153, 2017.
[Bibtex]

@article{lieto2016towards,
author = {Lieto, Antonio and Radicioni, Daniele P. and Rho, Valentina and Mensa, Enrico},
title = {{Towards a Unifying Framework for Conceptual Represention and Reasoning in Cognitive Systems}},
journal = {{Intelligenza Artificiale}},
volume = {11},
number = {2},
pages = {139-153},
year = {2017},
doi = {},
URL = {},
pdf = {http://delorean.di.unito.it/ls/papers/lieto2016towards.pdf}
}

A. Lieto, D. P. Radicioni, and V. Rho, “Dual PECCS: A Cognitive System for Conceptual Representation and Categorization,” Journal of experimental & theoretical artificial intelligence, vol. 29, iss. 2, pp. 433-452, 2017.
[Bibtex]

@article{lieto2016dual,
author = {Antonio Lieto and Daniele P. Radicioni and Valentina Rho},
title = {{Dual PECCS: A Cognitive System for Conceptual Representation and Categorization}},
journal = {Journal of Experimental \& Theoretical Artificial Intelligence},
volume = {29},
number = {2},
pages = {433-452},
year = {2017},
doi = {10.1080/0952813X.2016.1198934},
URL = {http://dx.doi.org/10.1080/0952813X.2016.1198934},
eprint = {http://dx.doi.org/10.1080/0952813X.2016.1198934},
pdf = {http://delorean.di.unito.it/ls/papers/lieto2016dual.pdf}
}

D. Colla, E. Mensa, and D. P. Radicioni, “Semantic Measures for Keywords Extraction,” in Ai*ia 2017 advances in artificial intelligence: xvith international conference of the italian association for artificial intelligence, bari, italy, november 14-17, 2017, proceedings, F. Esposito, R. Basili, S. Ferilli, and F. A. Lisi, Eds., Cham: Springer international publishing, 2017, p. 128–140.
[Bibtex]

@Inbook{colla2017semantic,
author = {Colla, Davide and Mensa, Enrico and Radicioni, Daniele P.},
editor = {Esposito, Floriana and Basili, Roberto and Ferilli, Stefano and Lisi, Francesca A.},
title = {{Semantic Measures for Keywords Extraction}},
bookTitle = {AI*IA 2017 Advances in Artificial Intelligence: XVIth International Conference of the Italian Association for Artificial Intelligence, Bari, Italy, November 14-17, 2017, Proceedings},
year = {2017},
publisher = {Springer International Publishing},
address = {Cham},
pages = {128--140},
abstract = {In this paper we introduce a minimalist hypothesis for
keywords extraction: keywords can be extracted from text documents by
considering concepts underlying document terms. Furthermore, central
concepts are individuated as the concepts that are more related to
title concepts. Namely, we propose five metrics, that are diverse in
essence, to compute the centrality of concepts in the document body
with respect to those in the title. We finally report about an
experimentation over a popular data set of human annotated news
articles; the results confirm the soundness of our hypothesis.},
isbn = {978-3-319-70169-1},
doi = {10.1007/978-3-319-70169-1_10},
pdf = {http://delorean.di.unito.it/ls/papers/colla17semantic.pdf}
}

A. Lieto, E. Mensa, and D. P. Radicioni, “A Resource-Driven Approach for Anchoring Linguistic Resources to Conceptual Spaces,” in XVth International Conference of the Italian Association for Artificial Intelligence, Genova, Italy, November 29 – December 1, 2016, Proceedings, 2016, p. 435–449.
[Bibtex]

@inproceedings{lieto2016resource,
Author = {Lieto, Antonio and Mensa, Enrico and Radicioni, Daniele P.},
Booktitle = {{XVth International Conference of the Italian Association for Artificial Intelligence, Genova, Italy, November 29 – December 1, 2016, Proceedings}},
Pages = {435--449},
Publisher = {Springer},
Series = {Lecture Notes in Artificial Intelligence},
Title = {{A Resource-Driven Approach for Anchoring Linguistic Resources to Conceptual Spaces}},
Volume = {10037},
DOI = {10.1007/978-3-319-49130-1},
ISBN = {978-3-319-49129-5},
Year = {2016},
pdf = {http://delorean.di.unito.it/ls/papers/lieto2016resource.pdf}
}

A. Lieto, E. Mensa, and D. P. Radicioni, “Taming Sense Sparsity: a Common-Sense Approach,” in Proceedings of Third Italian Conference on Computational Linguistics (CLiC-it 2016) & Fifth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian., 2016.
[Bibtex]

@inproceedings{lieto16taming,
author = {Antonio Lieto and
Enrico Mensa and
Daniele P. Radicioni},
title = {{Taming Sense Sparsity: a Common-Sense Approach}},
booktitle = {{Proceedings of Third Italian Conference on Computational Linguistics (CLiC-it 2016) {\&} Fifth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian.}},
year = {2016},
url = {http://ceur-ws.org/Vol-1749/paper31.pdf},
pdf = {http://delorean.di.unito.it/ls/papers/lieto16taming.pdf}
}

LS@DipInfo

Publications

Our publications