The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Knowledge Discovery from Transportation Network Data
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Efficient aggregation for graph summarization
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Truth Discovery with Multiple Conflicting Information Providers on the Web
IEEE Transactions on Knowledge and Data Engineering
Graph OLAP: Towards Online Analytical Processing on Graphs
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
RankClus: integrating clustering with ranking for heterogeneous information network analysis
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Ranking-based clustering of heterogeneous information networks with star network schema
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Integrative construction and analysis of condition-specific biological networks
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
iTopicModel: Information Network-Integrated Topic Modeling
ICDM '09 Proceedings of the 2009 Ninth IEEE International Conference on Data Mining
Community evolution detection in dynamic heterogeneous information networks
Proceedings of the Eighth Workshop on Mining and Learning with Graphs
Mining advisor-advisee relationships from research publication networks
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Graph regularized transductive classification on heterogeneous information networks
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
Global detection of complex copying relationships between sources
Proceedings of the VLDB Endowment
Social Network Data Analytics
Graph cube: on warehousing and OLAP multidimensional networks
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Probabilistic topic models with biased propagation on heterogeneous information networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Ranking-based classification of heterogeneous information networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Co-author Relationship Prediction in Heterogeneous Bibliographic Networks
ASONAM '11 Proceedings of the 2011 International Conference on Advances in Social Networks Analysis and Mining
The future of citeseer: citeseerx
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
When will it happen?: relationship prediction in heterogeneous information networks
Proceedings of the fifth ACM international conference on Web search and data mining
Relation strength-aware clustering of heterogeneous information networks with incomplete attributes
Proceedings of the VLDB Endowment
Modeling and exploiting heterogeneous bibliographic networks for expertise ranking
Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries
Relevance search in heterogeneous networks
Proceedings of the 15th International Conference on Extending Database Technology
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Query-driven discovery of semantically similar substructures in heterogeneous networks
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
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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.