@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}
}

@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}
}

@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}
}

@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}
}