Unpacking "privacy" for a networked world
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
An architecture for privacy-sensitive ubiquitous computing
Proceedings of the 2nd international conference on Mobile systems, applications, and services
What am I gonna wear?: scenario-oriented recommendation
Proceedings of the 12th international conference on Intelligent user interfaces
De-anonymizing Social Networks
SP '09 Proceedings of the 2009 30th IEEE Symposium on Security and Privacy
Introduction to social recommendation
Proceedings of the 19th international conference on World wide web
Tailoring collaboration according privacy needs in real-identity collaborative systems
CRIWG'09 Proceedings of the 15th international conference on Groupware: design, implementation, and use
Selecting keywords for content based recommendation
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
A recommender system for assistive environments
Proceedings of the 4th International Conference on PErvasive Technologies Related to Assistive Environments
Towards Transparent Anonymity for User-controlled Servers Supporting Collaborative Scenarios
ITNG '12 Proceedings of the 2012 Ninth International Conference on Information Technology - New Generations
Privacy-preserving concepts for supporting recommendations in decentralized OSNs
Proceedings of the 4th International Workshop on Modeling Social Media
Trust and privacy in the di.me userware
HCI'13 Proceedings of the 15th international conference on Human-Computer Interaction: users and contexts of use - Volume Part III
Towards visual configuration support for interdependent security goals
OCSC'13 Proceedings of the 5th international conference on Online Communities and Social Computing
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New trends in pervasive computing allow for hosting user controlled servers for integrating respective user's social spheres. One main feature of such servers is the provision of a single point for managing user's data and resources from various social interaction services (e.g., LinkedIn, Facebook, etc.). A step forward would be to include the collection and integration of different social contacts and their live streams (e.g., activity status, live posts, etc.) from these services. Thereby, various privacy issues related to linkability and unwanted information disclosure, could arise. In this paper, we address how we intend to avoid such privacy issues in the EU FP7 funded di.me project when mining users' social spheres from different sources. Our approach uses (1) the detection of semantic equivalence between contacts as portrayed in online profiles and (2) NLP techniques for analysing shared live streams both; for triggering privacy recommendations. The current status is presented and the portability to other environments is shortly discussed.