Abstract
Reputation, influenced by ratings from past clients, is crucial for providers competing for custom. For new providers with less track record, a few negative ratings can harm their chances of growing. Aside from malicious or subjective ratings, addressed in existing work, an honest balanced review of a service provision may still be an unreliable predictor of future performance if the circumstances differ. For example, while a delivery service may be generally reliable, a particular delivery may be delayed by flooding. A common way to ameliorate the ratings that may not reflect future performance is by weighting by recency. We argue that better results are obtained by querying records of how services are provided for patterns indicating the circumstances of provision, to determine the significance of past interactions.
Original language | English |
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Title of host publication | Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS |
Publisher | International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS) |
Pages | 1653-1654 |
Number of pages | 2 |
Volume | 3 |
ISBN (Print) | 9781450337717 |
Publication status | Published - 2015 |
Event | 14th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015 - Istanbul, Turkey Duration: 4 May 2015 → 8 May 2015 |
Conference
Conference | 14th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015 |
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Country/Territory | Turkey |
City | Istanbul |
Period | 4/05/2015 → 8/05/2015 |
Keywords
- Circumstances
- Reputation
- Trust provenance