Distributional-Relational Models: Scalable Semantics for Databases
Refereed Conference Meeting Proceeding
The crisp/brittle semantic model behind databases lim- its the scale in which data consumers can query, ex- plore, integrate and process structured data. Approaches aiming to provide more comprehensive semantic mod- els for databases, which are purely logic-based (e.g. as in Semantic Web databases) have major scalability lim- itations in the acquisition of structured semantic and commonsense data. This work describes a complemen- tary semantic model for databases which has seman- tic approximation at its center. This model uses distri- butional semantic models (DSMs) to extend structured data semantics. DSMs support the automatic construc- tion of semantic and commonsense models from large- scale unstructured text and provides a simple model to analyze similarities in the structured data. The combi- nation of distributional and structured data semantics provides a simple and promising solution to address the challenges associated with the interaction and process- ing of structured data.
AAAI Spring Symposium Series (SSS-15)
Digital Object Identifer (DOI):
United States of America
National University of Ireland, Galway (NUIG)
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