In this paper, we propose an approach based on Bayesian networks (BNs) for building recommender systems that minimize context acquisition. Our learning approach ...
Discovering and Exploiting Causal Dependencies for Robust MobileContext-Aware Recommenders. (2007).IEEE Transactions on Knowledge and Data Engineering. 19 ...
This paper introduces a scalable mechanism based on Bayesian network learning in a tiered context model to overcome both of these challenges. Extensive ...
Missing: Robust | Show results with:Robust
Mobile context-aware recommender systems face unique challenges in acquiring context. Resource limitations make minimizing context acquisition a practical ...
This paper introduces a scalable mechanism based on Bayesian network learning in a tiered context model to overcome both of these challenges. Extensive ...
Missing: Robust | Show results with:Robust
Bibliographic details on Discovering and Exploiting Causal Dependencies for Robust Mobile Context-Aware Recommenders.
Discovering Causal Dependencies in Mobile Context-Aware ...
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Mobile context-aware recommender systems face unique challenges in acquiring context. Resource limitations make minimizing context acquisition a practical need, ...
... Contexts and Exploiting the Context Dependencies for Robust Recommendations. 3.1 Preliminaries . 34. 35. 3.1.1. Context-Aware Content-Based Recommender ... Causal ...
Although markers are unavail- able, our two-tiered context model can effectively capture the causal dependencies by including also those word attributes that ...
1992. Discovering and exploiting causal dependencies for robust mobile context-aware recommenders. GE Yap, AH Tan, HH Pang. IEEE Transactions on Knowledge and ...