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Mining heterogeneous information networks

Authors :
Yizhou Sun
Jiawei Han
Source :
ACM SIGKDD Explorations Newsletter. 14:20-28
Publication Year :
2013
Publisher :
Association for Computing Machinery (ACM), 2013.

Abstract

Most objects and data in the real world are of multiple types, interconnected, forming complex, heterogeneous but often semi-structured information networks. However, most network science researchers are focused on homogeneous networks, without distinguishing different types of objects and links in the networks. We view interconnected, multityped data, including the typical relational database data, as heterogeneous information networks, study how to leverage the rich semantic meaning of structural types of objects and links in the networks, and develop a structural analysis approach on mining semi-structured, multi-typed heterogeneous information networks. In this article, we summarize a set of methodologies that can effectively and efficiently mine useful knowledge from such information networks, and point out some promising research directions.

Details

ISSN :
19310153 and 19310145
Volume :
14
Database :
OpenAIRE
Journal :
ACM SIGKDD Explorations Newsletter
Accession number :
edsair.doi...........ef591f8c5106248d35c3a0039dd7a949