Information Integration for Graph Databases
With increasing interest in querying and analyzing graph data from multiple sources, algorithms and tools to integrate different graphs become very important. Integration of graphs can take place at the schema and instance levels. While links among graph nodes pose additional challenges to graph information integration, they can also serve as useful features for matching nodes representing real-world entities. This chapter introduces a general framework to perform graph information integration. It then gives an overview of the state-of-the-art research and tools in graph information integration.
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
Link Mining: Models, Algorithms, and Applications
Philip S. Yu, Christos Faloutsos, and Jiawei Han
City or Country
LIM, Ee Peng; SUN, Aixin; Datta, Anwitaman; and Kuiyu, CHANG.
Information Integration for Graph Databases. (2010). Link Mining: Models, Algorithms, and Applications. 265-281. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1340