Capturing reputation features in multiagent systems through emerging patterns
Multiagent systems and online communities rely on rating systems to infer the reputation given to an individual within a particular context. The notion of reputation is essential for helping a given individual to trust in other individuals and for being himself reliable to others. Current techniques...
Guardado en:
| Autores principales: | , |
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2005
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/21158 |
| Aporte de: |
| Sumario: | Multiagent systems and online communities rely on rating systems to infer the reputation given to an individual within a particular context. The notion of reputation is essential for helping a given individual to trust in other individuals and for being himself reliable to others. Current techniques for computing individual’s reputations are solely based on recent activities, facilitating a variety of possible attacks. Moreover, the amount of trust each agent has for a given context is based just on his or her reputation. In this paper we outline a new way to thwart reputation-based attacks and to detect trends in behavioral patterns based on historical data by means of knowledge discovery techniques, particularly those existing for emerging patterns. |
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