no code implementations • EACL 2017 • Debora Nozza, Fausto Ristagno, Matteo Palmonari, Elisabetta Fersini, Manch, Pikakshi a, Enza Messina
In this paper we present TWINE, a real-time system for the big data analysis and exploration of information extracted from Twitter streams.
1 code implementation • 5 Jun 2019 • Valerio Di Carlo, Federico Bianchi, Matteo Palmonari
Temporal word embeddings have been proposed to support the analysis of word meaning shifts during time and to study the evolution of languages.
1 code implementation • 13 Apr 2020 • Federico Bianchi, Valerio Di Carlo, Paolo Nicoli, Matteo Palmonari
In this paper, we present a general framework to support cross-corpora language studies with word embeddings, where embeddings generated from different corpora can be compared to find correspondences and differences in meaning across the corpora.
no code implementations • 30 Apr 2020 • Federico Bianchi, Gaetano Rossiello, Luca Costabello, Matteo Palmonari, Pasquale Minervini
Knowledge graph embeddings are now a widely adopted approach to knowledge representation in which entities and relationships are embedded in vector spaces.
1 code implementation • International Semantic Web Conference (ISWC) 2020 • Vincenzo Cutrona, Federico Bianchi, Ernesto Jimenez-Ruiz, Matteo Palmonari
Table annotation is a key task to improve querying the Web and support the Knowledge Graph population from legacy sources (tables).
1 code implementation • EMNLP 2021 • Federico Bianchi, Marco Marelli, Paolo Nicoli, Matteo Palmonari
Understanding differences of viewpoints across corpora is a fundamental task for computational social sciences.
1 code implementation • LREC 2022 • Giorgio Ottolina, Matteo Palmonari, Mehwish Alam, Manuel Vimercati
To the best of our knowledge, this is the first study that examines the metaphor detection task with a detailed exploratory analysis where different temporal and static word embeddings are used to account for different representations of literal meanings.
no code implementations • 17 Mar 2022 • Marco Ripamonti, Flavio De Paoli, Matteo Palmonari
The large availability of datasets fosters the use of \acrshort{ml} and \acrshort{ai} technologies to gather insights, study trends, and predict unseen behaviours out of the world of data.