QoS-based reputation feedback fusion under unknown correlation

Mohamad Mehdi, Nizar Bouguila, Jamal Bentahar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


Due to the flood of web services that offer similar functionalities, service consumers are left with a challenging selection decision. A popular approach to assist them with the service selection task is based on the reputation of web services. However, the propagation of reputation feedback in an open and distributed system of web services yield correlated reputation estimates. The existing web service reputation literature still lacks a system that handles the aggregation of reputation feedback under unknown correlation. To fill this gap, we employ two data fusion algorithms, the covariance intersection and ellipsoidal intersection, to aggregate QoS-based reputation feedback. Our experimental results endorse the advantageous capability and scalability of the proposed methods in aggregating reputation estimates, and show an enhanced performance when compared with the Kalman filter method.

Original languageBritish English
Title of host publicationAdaptive and Intelligent Systems - Third International Conference, ICAIS 2014, Proceedings
PublisherSpringer Verlag
Number of pages10
ISBN (Print)9783319112978
StatePublished - 2014
Event3rd International Conference on Adaptive and Intelligent Systems, ICAIS 2014 - Bournemouth, United Kingdom
Duration: 8 Sep 201410 Sep 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8779 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference3rd International Conference on Adaptive and Intelligent Systems, ICAIS 2014
Country/TerritoryUnited Kingdom


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