Zobrazeno 1 - 10
of 98
pro vyhledávání: '"Roberto De Prisco"'
Publikováno v:
Applied Sciences, Vol 12, Iss 21, p 11209 (2022)
Music is widely used for mood and emotion regulation in our daily life. As a result, many research works on music information retrieval and affective human-computer interaction have been proposed to model the relationships between emotion and music.
Externí odkaz:
https://doaj.org/article/c69dc9cc02cc4c85b742b675cc1e3796
Autor:
Alberto Cosimato, Roberto De Prisco, Alfonso Guarino, Delfina Malandrino, Nicola Lettieri, Giuseppe Sorrentino, Rocco Zaccagnino
Publikováno v:
IEEE Access, Vol 7, Pp 123289-123298 (2019)
Nowadays social media are the main means for conducting discussions and sharing opinions. The huge amount of information generated by social media users is helpful for predicting outcomes of real-world events in different fields, including business,
Externí odkaz:
https://doaj.org/article/71c6243e20854d93bf8e5beaa860b3f3
Publikováno v:
IEEE Transactions on Dependable and Secure Computing. :1-15
Publikováno v:
Data Mining and Knowledge Discovery. 36:1301-1334
Plagiarism is a controversial and debated topic in different fields, especially in the Music one, where the commercial market generates a huge amount of money. The lack of objective metrics to decide whether a song is a plagiarism, makes music plagia
Autor:
Roberto De Prisco, Rocco Zaccagnino
Publikováno v:
Soft Computing. 26:9689-9706
Splicing systems are a form of DNA computing as they mimic the recombination process among DNA molecules. This work discusses the use of splicing systems to build automatic tools for reproducing human beings’ creativity, in the context of automatic
Publikováno v:
IEEE Transactions on Dependable and Secure Computing. :1-15
Publikováno v:
Journal of Information Security and Applications. 75:103479
Autor:
Delfina Malandrino, Roberto De Prisco, Gerardo Benevento, Nicola Lettieri, Rocco Zaccagnino, Alfonso Guarino
Publikováno v:
IV
Several works on representation learning for graph-structured data have been proposed in recent literature. However, most of such techniques have several downsides. On the one hand, graph kernels which use handcrafted features (e.g., shortest paths)
We propose a new design technique for constructing secret sharing schemes over a potentially infinite set of participants. Our findings leverage on a nice property of secret sharing schemes for finite sets of participants based on the Chinese remaind
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8ef1acf5826021747b998e8e37ddd62
http://hdl.handle.net/11386/4765122
http://hdl.handle.net/11386/4765122