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Giulio Petrucci
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2010 – 2019
- 2018
- [b1]Giulio Petrucci:
Learning to Learn Concept Descriptions. University of Trento, Italy, 2018 - [j3]Mauro Dragoni, Giulio Petrucci
:
A fuzzy-based strategy for multi-domain sentiment analysis. Int. J. Approx. Reason. 93: 59-73 (2018) - [j2]Giulio Petrucci, Marco Rospocher
, Chiara Ghidini:
Expressive ontology learning as neural machine translation. J. Web Semant. 52-53: 66-82 (2018) - [c9]Eleonora Grilli
, Domenica Dininno, Lucia Marsicano, Giulio Petrucci, Fabio Remondino
:
Supervised segmentation of 3D cultural heritage. DigitalHERITAGE/VSMM 2018: 1-8 - [c8]Giulio Petrucci, Mauro Dragoni:
The IRMUDOSA System at ESWC-2018 Challenge on Semantic Sentiment Analysis. SemWebEval@ESWC 2018: 167-185 - 2017
- [j1]Mauro Dragoni
, Giulio Petrucci:
A Neural Word Embeddings Approach for Multi-Domain Sentiment Analysis. IEEE Trans. Affect. Comput. 8(4): 457-470 (2017) - [c7]Chiara Di Francescomarino, Chiara Ghidini, Fabrizio Maria Maggi, Giulio Petrucci, Anton Yeshchenko:
An Eye into the Future: Leveraging A-priori Knowledge in Predictive Business Process Monitoring. BPM 2017: 252-268 - [c6]Giulio Petrucci, Mauro Dragoni:
The IRMUDOSA System at ESWC-2017 Challenge on Semantic Sentiment Analysis. SemWebEval@ESWC 2017: 148-165 - 2016
- [c5]Giulio Petrucci, Chiara Ghidini, Marco Rospocher
:
Ontology Learning in the Deep. EKAW 2016: 480-495 - [c4]Giulio Petrucci, Mauro Dragoni
:
The IRMUDOSA System at ESWC-2016 Challenge on Semantic Sentiment Analysis. SemWebEval@ESWC 2016: 126-140 - [i1]Giulio Petrucci, Chiara Ghidini, Marco Rospocher:
Using Recurrent Neural Network for Learning Expressive Ontologies. CoRR abs/1607.04110 (2016) - 2015
- [c3]Giulio Petrucci, Mauro Dragoni
:
An Information Retrieval-Based System for Multi-domain Sentiment Analysis. SemWebEval@ESWC 2015: 234-243 - [c2]Giulio Petrucci:
Information Extraction for Learning Expressive Ontologies. ESWC 2015: 740-750 - [c1]Mauro Dragoni, Giulio Petrucci:
Supporting Multilingual Ontology Matching With MoKi. ISWC (Posters & Demos) 2015
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