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» Modeling the Propagation of User Preferences
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CCS
2010
ACM
14 years 2 months ago
Towards publishing recommendation data with predictive anonymization
Recommender systems are used to predict user preferences for products or services. In order to seek better prediction techniques, data owners of recommender systems such as Netfli...
Chih-Cheng Chang, Brian Thompson, Hui (Wendy) Wang...
ECAI
2008
Springer
14 years 22 days ago
A BDD Approach to the Feature Subscription Problem
Modern feature-rich telecommunications services offer significant opportunities to human users. To make these services more usable, facilitating personalisation is very important s...
Tarik Hadzic, David Lesaint, Deepak Mehta, Barry O...
LWA
2007
14 years 11 days ago
Context-adaptation based on Ontologies and Spreading Activation
Ontologies and spreading activation are known terms within the scope of information retrieval. In this paper we introduce SPREADR, an integrated adaptation mechanism for web appli...
Tim Hussein, Daniel Westheide, Jürgen Ziegler
ESWA
2008
152views more  ESWA 2008»
13 years 11 months ago
Collaborative recommender systems: Combining effectiveness and efficiency
Recommender systems base their operation on past user ratings over a collection of items, for instance, books, CDs, etc. Collaborative filtering (CF) is a successful recommendatio...
Panagiotis Symeonidis, Alexandros Nanopoulos, Apos...
JAIR
2010
130views more  JAIR 2010»
13 years 5 months ago
Interactive Cost Configuration Over Decision Diagrams
In many AI domains such as product configuration, a user should interactively specify a solution that must satisfy a set of constraints. In such scenarios, offline compilation of ...
Henrik Reif Andersen, Tarik Hadzic, David Pisinger