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» Probabilistic Models for Expert Finding
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UM
2005
Springer
14 years 1 months ago
ExpertiseNet: Relational and Evolutionary Expert Modeling
We develop a novel user-centric modeling technology, which can dynamically describe and update a person's expertise profile. In an enterprise environment, the technology can e...
Xiaodan Song, Belle L. Tseng, Ching-Yung Lin, Ming...
IJCAI
1989
13 years 9 months ago
Maximum Entropy in Nilsson's Probabilistic Logic
Nilsson's Probabilistic Logic is a set theoretic mechanism for reasoning with uncertainty. We propose a new way of looking at the probability constraints enforced by the fram...
Thomas B. Kane
ICDM
2007
IEEE
153views Data Mining» more  ICDM 2007»
14 years 2 months ago
HSN-PAM: Finding Hierarchical Probabilistic Groups from Large-Scale Networks
Real-world social networks are often hierarchical, reflecting the fact that some communities are composed of a few smaller, sub-communities. This paper describes a hierarchical B...
Haizheng Zhang, Wei Li, Xuerui Wang, C. Lee Giles,...
WSC
2007
13 years 10 months ago
Finite-sample performance guarantees for one-dimensional stochastic root finding
We study the one-dimensional root finding problem for increasing convex functions. We give gradient-free algorithms for both exact and inexact (stochastic) function evaluations. ...
Samuel Ehrlichman, Shane G. Henderson
UAI
2003
13 years 9 months ago
Bayesian Hierarchical Mixtures of Experts
The Hierarchical Mixture of Experts (HME) is a well-known tree-structured model for regression and classification, based on soft probabilistic splits of the input space. In its o...
Christopher M. Bishop, Markus Svensén