Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/68836
Título: | Generating real context data to test user dependent systems - application to multi-agent systems |
Autor(es): | Oliveira, Pedro Novais, Paulo Matos, Paulo |
Palavras-chave: | Adaptive-system AmI Multi-agent system Privacy Security Simulation |
Data: | 2019 |
Editora: | Springer Verlag |
Revista: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Citação: | Oliveira P., Novais P., Matos P. (2019) Generating Real Context Data to Test User Dependent Systems - Application to Multi-agent Systems. In: Demazeau Y., Matson E., Corchado J., De la Prieta F. (eds) Advances in Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection. PAAMS 2019. Lecture Notes in Computer Science, vol 11523. Springer, Cham. https://doi.org/10.1007/978-3-030-24209-1_15 |
Resumo(s): | This paper, deals with the usually need of data to simulate behavior and efficiency of proposed solutions in several fields, and also knowing that personal data always bring privacy and security issues. This work wants to promote a balanced solution between the need of personal information and the user’s privacy expectations. We propose a solution to overcome these issues, and don’t compromise the balance between security and personal comfort based on generating real context data of users, that allow to test user dependent systems. |
Tipo: | Artigo em ata de conferência |
Descrição: | First Online 26 June 2019 |
URI: | https://hdl.handle.net/1822/68836 |
ISBN: | 978-3-030-24208-4 |
e-ISBN: | 978-3-030-24209-1 |
DOI: | 10.1007/978-3-030-24209-1_15 |
ISSN: | 0302-9743 |
Versão da editora: | https://link.springer.com/chapter/10.1007%2F978-3-030-24209-1_15 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
---|---|---|---|---|
Paper_Simul_Users_PAAMS_2019.pdf | 359,36 kB | Adobe PDF | Ver/Abrir |