TY - GEN
T1 - Trust-based techniques for collective intelligence in social search systems
AU - Dondio, Pierpaolo
AU - Longo, Luca
PY - 2011
Y1 - 2011
N2 - A key-issue for the effectiveness of collaborative decision support systems is the problem of the trustworthiness of the entities involved in the process. Trust has been always used by humans as a form of collective intelligence to support effective decision making process. Computational trust models are becoming now a popular technique across many applications such as cloud computing, p2p networks, wikis, e-commerce sites, social network. The chapter provides an overview of the current landscape of computational models of trust and reputation, and it presents an experimental study case in the domain of social search, where we show how trust techniques can be applied to enhance the quality of social search engine predictions.
AB - A key-issue for the effectiveness of collaborative decision support systems is the problem of the trustworthiness of the entities involved in the process. Trust has been always used by humans as a form of collective intelligence to support effective decision making process. Computational trust models are becoming now a popular technique across many applications such as cloud computing, p2p networks, wikis, e-commerce sites, social network. The chapter provides an overview of the current landscape of computational models of trust and reputation, and it presents an experimental study case in the domain of social search, where we show how trust techniques can be applied to enhance the quality of social search engine predictions.
UR - https://www.scopus.com/pages/publications/79960939524
U2 - 10.1007/978-3-642-20344-2_5
DO - 10.1007/978-3-642-20344-2_5
M3 - Conference contribution
AN - SCOPUS:79960939524
SN - 9783642203435
T3 - Studies in Computational Intelligence
SP - 113
EP - 135
BT - Next Generation Data Technologies for Collective Computational Intelligence
A2 - Bessis, Nik
A2 - Xhafa, Fatos
ER -