Filtering and profiling techniques for mobile environment should be specified to take into account the difference between predictive and contextual attributes.
The problem of profiling and filtering is important particularly for mobile information systems where wireless network traffic and mobile terminal's size ...
Filtering and profiling techniques for mobile environment should be specified to take into account the difference between predictive and contextual attributes.
The Bayesian Metanetwork is considered as a useful tool to present the second order uncertainty and therefore to predict mobile user's preferences.
Two models of the Metanetwork are considered: C-Metanetwork for managing conditional dependencies and R-Metanetwork for modelling feature selection. The ...
In this paper Multilevel Bayesian belief networks were proposed for modeling of user preferences in the mobile information environment. Bayesian Metanetwork is ...
Six topologies of dynamic Bayesian Networks are evaluated for predicting the future user events and the results show that the number of user cases has high ...
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Aug 24, 2004 · The Bayesian Metanetwork is a set of Bayesian networks, which are put on each other in such a way that the elements (nodes or conditional ...
We use the Bayesian RN-Metanetwork to learn both user preference and priority at the same time, as well as to resolve the conflict among many user preferences.
In this paper, we propose an online approach for parameter learning of UPM. Specifically, we first extend the classic Voting EM algorithm by using Bayesian ...
Missing: Metanetworks Mobile