White Papers

Whitepaper Semantic Engine

AutorAndreas Lommatzsch, Jérôme Kunegis, Torsten Schmidt, Stefan Marx
QuelleDAI-Labor, TU-Berlin 

With the growing availability of semantic datasets, the processing of these dataset comes in the focus of interest. Thus, the efficient processing of large semantic datasets can improve application in many domains. In this whitepaper, we introduce an architecture that supports the aggregation of different types of semantic data and provides components for deriving recommendations and predicting relevant relationships between dataset entities. The developed architecture supports different types of data sources (e.g. databases, semantic networks) and enables the efficient processing of large semantic datasets with several different semantic relationship types. We discuss the developed architecture and describe an implemented application for the entertainment domain.