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Mostrando ítems 11-17 de 17
Application of machine learning algorithms for the validation of a new CoAP-IoT anomaly detection dataset
(MDPI, 2023-04)
[Abstract]: With the rise in smart devices, the Internet of Things (IoT) has been established as one of the preferred emerging platforms to fulfil their need for simple interconnections. The use of specific protocols such ...
Measuring Early Detection of Anomalies
(IEEE, 2022)
[Abstract] Early detection is a matter of growing importance in multiple domains as network security, health conditions over social network services or weather forecasts related disasters. It is not enough to make a good ...
Site agnostic approach to early detection of cyberbullying on social media networks
(MDPI, 2023-05)
[Abstract]: The rise in the use of social media networks has increased the prevalence of cyberbullying, and time is paramount to reduce the negative effects that derive from those behaviours on any social media platform. ...
Gaia Data Release 3: Catalogue validation
(EDP Sciences, 2023-06)
[Abstract]: Context. The third Gaia data release (DR3) provides a wealth of new data products. The early part of the release, Gaia EDR3, already provided the astrometric and photometric data for nearly two billion sources. ...
Time Aware F-Score for Cybersecurity Early Detection Evaluation
(MDPI, 2024-01)
[Abstract]: With the increase in the use of Internet interconnected systems, security has become of utmost importance. One key element to guarantee an adequate level of security is being able to detect the threat as soon ...
Gaia Focused Product Release: A catalogue of sources around quasars to search for strongly lensed quasars
(EDP Sciences, 2024-05-17)
[Abstract]: Context. Strongly lensed quasars are fundamental sources for cosmology. The Gaia space mission covers the entire sky with the unprecedented resolution of 0.18″ in the optical, making it an ideal instrument to ...
A Content-Based Approach to Profile Expansion
(World Scientific, 2020-12)
[Abstract]: Collaborative Filtering algorithms suffer from the so-called cold-start problem. In particular, when a user has rated few items, recommendations offered by these algorithms are not too accurate. Profile Expansion ...