Graph models do excel where data have an element of uncertainty or unpredictability and the relationships are data’s main features. However, existing graph models neglect the semantics of node and relationship type.

To capture as much semantics as possible, we extend the nodes in graph model with some object-oriented features and edges with multiple semantic information, and propose a Semantic Graph Model (SGM). SGM is a schema-less model and supports dynamic data structures as well as extra semantics. Although the class definition is unknown at the beginning, the schema can be extracted from the semi-structured and semantic data. The excavated domain model can help further data analysis and data fusion, and it is also important for graph query optimization.

We have proposed graph create statements to represent data in SGM and have implemented a conversion layer to store, manage and query the graph upon the graph database system, Neo4j.


Graph Model Relationship Type Graph Database Program Chair Class Node 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.State Key Lab of Software Engineering, School of ComputerWuhan UniversityWuhanChina

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