Mining Heterogeneous Information Networks

author: Jiawei Han, Department of Computer Science, University of Illinois at Urbana-Champaign
published: Sept. 27, 2013,   recorded: August 2013,   views: 7581


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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.

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Reviews and comments:

Comment1 Xinran, November 12, 2013 at 4:12 p.m.:

Is This actually a semantic web?

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