Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Recommending and evaluating choices in a virtual community of use
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Learning and Revising User Profiles: The Identification ofInteresting Web Sites
Machine Learning - Special issue on multistrategy learning
The Cathedral and the Bazaar
Editorial: Open Source and Empirical Software Engineering
Empirical Software Engineering
Succeeding with Open Source (Addison-Wesley Information Technology Series)
Succeeding with Open Source (Addison-Wesley Information Technology Series)
Computing and applying trust in web-based social networks
Computing and applying trust in web-based social networks
A collaborative filtering approach to predict web pages of interest from navigation patterns of past users within an academic website
Deriving Ratings Through Social Network Structures
ARES '06 Proceedings of the First International Conference on Availability, Reliability and Security
Software Process Maturity and the Success of Free Software Projects
Proceedings of the 2005 conference on Software Engineering: Evolution and Emerging Technologies
The QualiSPo approach to OSS product quality evaluation
Proceedings of the 3rd International Workshop on Emerging Trends in Free/Libre/Open Source Software Research and Development
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With the growing number of available Free and Open Source Software (F/OSS) applications, choosing between them becomes increasingly difficult. The concept of “trust” in social networking has been successfully applied to facilitate choice in similar situations. We propose a social network-based approach to quality assessment and evaluation of F/OSS applications. The proposed system utilises the community formed around F/OSS projects to produce meaningful recommendations based on specific user preferences. We suggest that such an approach would overcome some of the difficulties complicating user choice by making useful suggestions and can fit seamlessly within the structure of the majority of F/OSS projects. The main focus of this work is on the end users of free and open source software and not on the developers of the software. The social network-based approach would apply differently to these different user classes.