MiniCon: A scalable algorithm for answering queries using views
The VLDB Journal — The International Journal on Very Large Data Bases
Personalization of Queries in Database Systems
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Query Rewriting in the Semantic Web7
ICDEW '06 Proceedings of the 22nd International Conference on Data Engineering Workshops
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Foundations of preferences in database systems
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Using latency-recency profiles for data delivery on the web
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Fast contextual preference scoring of database tuples
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Context-Aware Computing Applications
WMCSA '94 Proceedings of the 1994 First Workshop on Mobile Computing Systems and Applications
Ranking Query Results using Context-Aware Preferences
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
Inferring user's preferences using ontologies
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Modelling context for information environments
UMICS'04 Proceedings of the Second CAiSE conference on Ubiquitous Mobile Information and Collaboration Systems
Introducing contexts into personalized web applications
Proceedings of the 12th International Conference on Information Integration and Web-based Applications & Services
DIY-CDR: an ontology-based, Do-It-Yourself component discoverer and recommender
Personal and Ubiquitous Computing
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Access to relevant information, adapted to user's needs, preferences and environment, is a challenge in many applications running in content delivery platforms, like IPTV, VoD and mobile Video. In order to provide users with personalized content, applications use various techniques such as content recommendation, content filtering, preference-driven queries, etc. These techniques exploit different knowledge organized into profiles and contexts. However, there is not a common understanding of these concepts and there is no clear foundation of what a personalized access model should be. This paper contributes to this concern by providing, through a meta model, a clear distinction between profile and context, and by providing a set of services which constitutes a basement to the definition of a personalized access model (PAM). Our PAM definition allows applications to interoperate in multiple personalization scenarios, including, preference-based recommendation, context-aware content delivery, personalized access to multiple contents, etc. Concepts and services proposed are tightly defined with respect to real applications requirements provided by Alcatel-Lucent.