Information integration for graph databases

Author

Ee Peng LIM, Singapore Management UniversityFollow
Aixin SUN
Anwitaman DATTA
CHANG KUIYU

Publication Type

Book Chapter

Version

acceptedVersion

Publication Date

2010

Abstract

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.

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Publication

Link Mining: Models, Algorithms, and Applications

Editor

Philip S. Yu, Christos Faloutsos, and Jiawei Han

First Page

265

Last Page

281

ISBN

9781441965158

Identifier

10.1007/978-1-4419-6515-8_10

Publisher

Springer Verlag

City or Country

New York

Citation

LIM, Ee Peng; SUN, Aixin; DATTA, Anwitaman; and KUIYU, CHANG. Information integration for graph databases. (2010). Link Mining: Models, Algorithms, and Applications. 265-281.
Available at: https://ink.library.smu.edu.sg/sis_research/1340

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.

Comments

Philip S. Yu, Jiawei Han, Christos Faloutsos

Additional URL

http://doi.org/10.1007/978-1-4419-6515-8_10