Distributed Relational Learning for Cloud Data Fusion

CCRi will enhance the utility of large-scale, geographically separated, semantic datasets by developing distributed capabilities for level 1 (entity resolution) and level 2 (inference) data fusion. CCRi will extend the model training server developed in Phase I, as well as the advanced techniques for concept extraction and visualization of large-scale semantic datasets developed during a parallel effort, to support streaming data, Map/Reduce model training, and integration with enriched data providers, as well as simplified model training. Models which incorporate temporal information will enable advanced predictive capabilities for relationships and concepts over time, which CCRi will investigate during Phase II. CCRi's primary focus in Phase II will be on the fusion of multiple models trained independently on distinct data sources, enabling model sharing without full data sharing, and fusion across clouds.