Analyzing Time-Evolving Networks using an Evolving Cluster Mixed Membership Blockmodel
نویسندگان
چکیده
23.
منابع مشابه
Co-Evolving Mixed Membership BlockModels
Many networks are complex dynamical systems, where both attributes of nodes and topology of the network (links structure) can change with time. We propose a model of co-evolving networks where both node attributes and network structure evolve under mutual influence. Specifically, we consider a mixed membership stochastic blockmodel, where the probability of observing a link between two nodes de...
متن کاملA State-space Mixed Membership Blockmodel for Dynamic Network Tomography By
In a dynamic social or biological environment, the interactions between the actors can undergo large and systematic changes. In this paper we propose a model-based approach to analyze what we will refer to as the dynamic tomography of such time-evolving networks. Our approach offers an intuitive but powerful tool to infer the semantic underpinnings of each actor, such as its social roles or bio...
متن کاملOnline Inference of Mixed Membership Stochastic Blockmodels for Network Data Streams
Many kinds of data can be represented as a network or graph. It is crucial to infer the latent structure underlying such a network and to predict unobserved links in the network. Mixed Membership Stochastic Blockmodel (MMSB) is a promising model for network data. Latent variables and unknown parameters in MMSB have been estimated through Bayesian inference with the entire network; however, it i...
متن کاملEvolving Cluster Mixed-Membership Blockmodel for Time-Evolving Networks
Time-evolving networks are a natural representation for dynamic social and biological interactions. While latent space models are gaining popularity in network modeling and analysis, previous works mostly ignore networks with temporal behavior and multi-modal actor roles. Furthermore, prior knowledge, such as division and grouping of social actors or biological specificity of molecular function...
متن کاملEvolving Cluster Mixed-Membership Blockmodel for Time-Varying Networks
Time-evolving networks are a natural representation for dynamic social and biological interactions. While latent space models are gaining popularity in network modeling and analysis, previous works mostly ignore networks with temporal behavior and multi-modal actor roles. Furthermore, prior knowledge, such as division and grouping of social actors or biological specificity of molecular function...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2014