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: 7574
Categories

Slides

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

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.

See Also:

Download slides icon Download slides: kdd2013_han_heterogeneous_information_01.pdf (6.5┬áMB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Reviews and comments:

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

Is This actually a semantic web?

Write your own review or comment:

make sure you have javascript enabled or clear this field: