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Yun Chi
Researcher at University of California, Los Angeles
Publications - 66
Citations - 6287
Yun Chi is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Tree structure & Cloud computing. The author has an hindex of 38, co-authored 66 publications receiving 6007 citations. Previous affiliations of Yun Chi include University of California.
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Proceedings ArticleDOI
Facetnet: a framework for analyzing communities and their evolutions in dynamic networks
TL;DR: This paper proposes FacetNet, a novel framework for analyzing communities and their evolutions through a robust unified process, where communities not only generate evolutions, they also are regularized by the temporal smoothness of evolutions.
Proceedings ArticleDOI
Combining link and content for community detection: a discriminative approach
TL;DR: A discriminative model for combining the link and content analysis for community detection from networked data, such as paper citation networks and Word Wide Web is proposed and introduced and hidden variables are introduced to explicitly model the popularity of nodes.
Proceedings ArticleDOI
Evolutionary spectral clustering by incorporating temporal smoothness
TL;DR: This paper proposes two frameworks that incorporate temporal smoothness in evolutionary spectral clustering and demonstrates that their methods provide the optimal solutions to the relaxed versions of the corresponding evolutionary k-means clustering problems.
Proceedings ArticleDOI
Moment: maintaining closed frequent itemsets over a stream sliding window
TL;DR: A compact data structure, the closed enumeration tree (CET), is introduced, to maintain a dynamically selected set of item-sets over a sliding-window that consists of a boundary between closed frequent itemsets and the rest of the itemsets.
Journal ArticleDOI
Detecting communities and their evolutions in dynamic social networks--a Bayesian approach
TL;DR: This paper proposes a dynamic stochastic block model for finding communities and their evolution in a dynamic social network that captures the evolution of communities by explicitly modeling the transition of community memberships for individual nodes in the network.