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AI
2009
Springer
16 years 1 months ago
Context Dependent Movie Recommendations Using a Hierarchical Bayesian Model
Abstract. We use a hierarchical Bayesian approach to model user preferences in different contexts or settings. Unlike many previous recommenders, our approach is content-based. We...
Daniel Pomerantz, Gregory Dudek
BPM
2008
Springer
144views Business» more  BPM 2008»
15 years 8 months ago
Supporting Flexible Processes through Recommendations Based on History
Abstract. In today's fast changing business environment flexible Process Aware Information Systems (PAISs) are required to allow companies to rapidly adjust their business pro...
Helen Schonenberg, Barbara Weber, Boudewijn F. van...
SIGIR
2011
ACM
14 years 9 months ago
Collaborative competitive filtering: learning recommender using context of user choice
While a user’s preference is directly reflected in the interactive choice process between her and the recommender, this wealth of information was not fully exploited for learni...
Shuang-Hong Yang, Bo Long, Alexander J. Smola, Hon...
CVPR
2012
IEEE
13 years 9 months ago
Model recommendation for action recognition
Simply choosing one model out of a large set of possibilities for a given vision task is a surprisingly difficult problem, especially if there is limited evaluation data with whi...
Pyry Matikainen, Rahul Sukthankar, Martial Hebert
WWW
2005
ACM
16 years 7 months ago
TrustGuard: countering vulnerabilities in reputation management for decentralized overlay networks
Reputation systems have been popular in estimating the trustworthiness and predicting the future behavior of nodes in a large-scale distributed system where nodes may transact wit...
Mudhakar Srivatsa, Li Xiong, Ling Liu