eprintid: 2095
rev_number: 6
eprint_status: archive
userid: 6
dir: disk0/00/00/20/95
datestamp: 2014-01-17 13:49:15
lastmod: 2014-01-17 13:49:15
status_changed: 2014-01-17 13:49:15
type: book_section
metadata_visibility: show
creators_name: Jøsang, Audun
creators_name: Quattrociocchi, Walter
creators_id: 
creators_id: walter.quattrociocchi@imtlucca.it
title: Advanced features in Bayesian reputation systems
ispublished: pub
subjects: QA75
divisions: CSA
full_text_status: none
note: 6th International Conference, TrustBus 2009, Linz, Austria, September 3-4, 2009. Proceedings
abstract: Bayesian reputation systems are quite flexible and can relatively easily be adapted to different types of applications and environments. The purpose of this paper is to provide a concise overview of the rich set of features that characterizes Bayesian reputation systems. In particular we demonstrate the importance of base rates during bootstrapping, for handling rating scarcity and for expressing long term trends
date: 2009
series: Lecture Notes in Computer Science
number: 5695
publisher: Springer 
pagerange: 105-114
id_number: 10.1007/978-3-642-03748-1_11
refereed: TRUE
isbn: 978-3-642-03748-1
book_title: Trust, Privacy and Security in Digital Business
official_url: http://dx.doi.org/10.1007/978-3-642-03748-1_11
citation:   Jøsang, Audun and Quattrociocchi, Walter  Advanced features in Bayesian reputation systems.   In:  Trust, Privacy and Security in Digital Business.   Lecture Notes in Computer Science  (5695).  Springer , pp. 105-114.  ISBN 978-3-642-03748-1      (2009)