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These are some of my publications as a researcher in Machine Learning and Natural Language Processing:

Cardellino, C., and Carrascosa, R. 2022. “A Study on Title Encoding Methods for E-Commerce Downstream Tasks”. The International FLAIRS Conference Proceedings 35 (May). [PDF]

Cardellino, C., and Carrascosa, R. 2021. “A Study on Multiple Tasks for E-Commerce Marketplaces”. The International FLAIRS Conference Proceedings 34 (April). [PDF]

Furman, D. A., Marro, S., Cardellino, C, Popa, D. N., Alonso Alemany, L. “You can simply rely on communities for a robust characterization of stances”. Florida Artificial Intelligence Research Society, LibraryPress@UF, 2021, 34 (1), ⟨10.32473/flairs.v34i1.128515⟩. ⟨hal-03260142⟩

Cardellino, C., Alonso Alemany, L., Teruel, M., Villata, S., and Marro, S. “Convolutional ladder networks for Legal NERC and the impact of unsupervised data in better generalizations.” In The Thirty-Second International Flairs Conference. 2019.

Teruel, M., Cardellino, C., Cardellino, F., Alonso Alemany, L., and Villata, S. “Legal text processing within the MIREL project.” In 1st Workshop on Language Resources and Technologies for the Legal Knowledge Graph, p. 42. 2018.

Teruel, M., Cardellino, C., Cardellino F., Alonso Alemany, L. and Villata, S., 2018, May. Increasing Argument Annotation Reproducibility by Using Inter-annotator Agreement to Improve Guidelines. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018).

Cardellino, C. and Alonso Alemany, L. Exploring the impact of word embeddings for disjoint semisupervised Spanish verb sense disambiguation. Inteligencia Artificial, [S.l.], v. 21, n. 61, p. 67-81, mar. 2018. ISSN 1988-3064.

Cardellino, C., Teruel, M., Alonso Alemany, L. and Villata, S., 2017, June. A Low-cost, High-coverage Legal Named Entity Recognizer, Classifier and Linker. In 16th International Conference on Artificial Intelligence and Law (ICAIL-2017).

Cardellino, C., Teruel, M., Alonso Alemany, L., and Villata, S. “Ontology Population and Alignment for the Legal Domain: YAGO, Wikipedia and LKIF.” In ISWC (Posters, Demos & Industry Tracks). 2017.

Cardellino, C., Teruel, M., Alonso Alemany, L. and Villata, S., 2017. Legal NERC with ontologies, Wikipedia and curriculum learning. EACL 2017, p.254. Teruel, M. and Cardellino, C., In-domain or out-domain word embeddings? A study for Legal Cases. ESSLLI 2017 Student Session, p.232.

Cardellino, C., Milagro Teruel, Laura Alonso Alemany, and Serena Villata. “Learning Slowly To Learn Better: Curriculum Learning for Legal Ontology Population.” In The Thirtieth International Flairs Conference. 2017.

Cardellino, C., A Study of Semi-Supervised Spanish Verb Sense Disambiguation. ESSLLI 2015 Student Session, p.175.

Cardellino, C., Villata, S., Alonso Alemany, L. and Cabrio, E., 2015, April. Information extraction with active learning: A case study in legal text. In Proceedings of the 16th International Conference on Intelligence Text Processing and Computational Linguistics (CICLing 2015).

Cardellino, C., Villata, S., Gandon, F., Governatori, G., Lam, H.P. and Rotolo, A., 2014, October. Licentia: a tool for supporting users in data licensing on the web of data. In Proceedings of the 2014 International Conference on Posters & Demonstrations Track-Volume 1272 (pp. 277-280). CEUR-WS. org.


Cristian Cardellino

Notes of a Computer Scientist

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