… In this paper, we combine the probabilistic graphical model with a probabilistic topic model
… in a probabilistic model. A Markov network is an undirected graph whose links represents …

… In our work, the discovery of meta-communities is treated as an optimization … probability
distributions over meta-communities, and meta-communities are, in turn, modeled as probability …

… have focused on probabilistic models of textual content for … discovery with topic modeling
in a unified generative model … have proposed probabilistic schemes that incorporate users' …

… in [6–8] by using probabilistic graphic modeling [19] to seamlessly … discovery and
probabilistic modeling. This led to the development of an intuitive and realistic generative model of …

… In this paper, we propose a new model of discovering communities of users on social … the
topic model combined with Kohonen network. In the proposed model, we focus on discovering …

… the models, which is concordant with the online nature of social streams. Experiments using
real-world data show the effectiveness of our model at discovering … probabilistic models are …

… Other works use generative probabilistic modeling which considers both contents and links
… model of the terms used by Twitter accounts and are more focused on similarity discovery …

… a probabilistic model called ErLinkTopic that is an extension of the rLinkTopic model developed
… A probabilistic model is developed to discover communities in each snapshot, which is …

… A similar probabilistic modeling is adopted for the susceptibility and authoritativeness of
com… Unfortunately, as it generally happens with probabilistic models of practical interest, exact …

… to promote strong relationships and participation among the members in e-communities. …
This research also discovered perceived trust as a vital virtual world element. Managers and …