Latent graphical models for quantifying and predicting patent quality.
Yan LiuPei-yun HseuhRick LawrenceSteve MeliksetianClaudia PerlichAlejandro VeenPublished in: KDD (2011)
Keyphrases
- graphical models
- belief propagation
- probabilistic model
- random variables
- approximate inference
- probabilistic inference
- bayesian networks
- probabilistic graphical models
- conditional dependencies
- markov networks
- conditional random fields
- latent variables
- map inference
- factor graphs
- conditional independence
- exact inference
- structure learning
- information retrieval
- belief networks
- graph structure
- statistical inference
- loopy belief propagation
- higher order
- undirected graphical models
- chain graphs
- maximum likelihood