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» Probabilistic Models for Expert Finding
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UM
2005
Springer
15 years 12 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...
147
Voted
IJCAI
1989
15 years 7 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
194
Voted
ICDM
2007
IEEE
153views Data Mining» more  ICDM 2007»
16 years 20 days 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,...
159
Voted
WSC
2007
15 years 8 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
206
Voted
UAI
2003
15 years 7 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