Abstract
The problem of encouraging trustworthy behavior in P2P online communities by managing peers’ reputations has drawn a lot of attention recently. However, most of the proposed solutions exhibit the following two problems: huge implementation overhead and unclear trust related model semantics. In this paper we show that a simple probabilistic technique, maximum likelihood estimation namely, can reduce these two problems substantially when employed as the feedback aggregation strategy. Thus, no complex exploration of the feedback is necessary. Instead, simple, intuitive and efficient probabilistic estimation methods suffice.
The work presented in this paper was partly carried out in the framework of the EPFL Center for Global Computing and supported by the Swiss National Funding Agency OFES as part of the European project Evergrow No 001935.
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Despotovic, Z., Aberer, K. (2004). A Probabilistic Approach to Predict Peers’ Performance in P2P Networks. In: Klusch, M., Ossowski, S., Kashyap, V., Unland, R. (eds) Cooperative Information Agents VIII. CIA 2004. Lecture Notes in Computer Science(), vol 3191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30104-2_6
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DOI: https://doi.org/10.1007/978-3-540-30104-2_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23170-7
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