Mining heterogeneous information networks
Northeastern University · University of Illinois Urbana-Champaign
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…
Citation impact
- FWCI
- 16.98
- Percentile
- 100%
- References
- 32
Authors
2Topics & keywords
- Computer science
- Leverage (statistics)
- Homogeneous
- Data science
- Heterogeneous network
- Set (abstract data type)
- Data mining
- Artificial intelligence