LiteMat: A scalable, cost-efficient inference encoding scheme for large RDF graphs.
Olivier CuréHubert NaackeTendry RandriamalalaBernd AmannPublished in: IEEE BigData (2015)
Keyphrases
- encoding scheme
- efficient inference
- rdf graphs
- probabilistic inference
- fully connected
- conditional random fields
- markov random field
- human pose estimation
- genetic algorithm
- hidden variables
- approximate inference
- structured prediction
- semantic web
- graph structure
- exact inference
- distributed systems
- multi dimensional
- dimensionality reduction
- data analysis