The anatomy of a large-scale hypertextual Web search engine
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On power-law relationships of the Internet topology
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Authoritative sources in a hyperlinked environment
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A Min-max Cut Algorithm for Graph Partitioning and Data Clustering
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
SimRank: a measure of structural-context similarity
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Normalized Cuts and Image Segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A study of smoothing methods for language models applied to information retrieval
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Probabilistic author-topic models for information discovery
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A cross-collection mixture model for comparative text mining
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Object-level ranking: bringing order to Web objects
WWW '05 Proceedings of the 14th international conference on World Wide Web
Multi-way distributional clustering via pairwise interactions
ICML '05 Proceedings of the 22nd international conference on Machine learning
Spectral clustering for multi-type relational data
ICML '06 Proceedings of the 23rd international conference on Machine learning
SCAN: a structural clustering algorithm for networks
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CSV: visualizing and mining cohesive subgraphs
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Efficient aggregation for graph summarization
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A general optimization framework for smoothing language models on graph structures
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RankClus: integrating clustering with ranking for heterogeneous information network analysis
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Probabilistic latent semantic analysis
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
iNextCube: information network-enhanced text cube
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Mining Heterogeneous Information Networks by Exploring the Power of Links
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Mining knowledge from databases: an information network analysis approach
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Community evolution detection in dynamic heterogeneous information networks
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Ranking of wireless access networks for providing QoS in heterogeneous environment
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Mining topic-level influence in heterogeneous networks
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
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
WINACS: construction and analysis of web-based computer science information networks
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Collective topic modeling for heterogeneous networks
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A game theoretic framework for heterogenous information network clustering
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Probabilistic topic models with biased propagation on heterogeneous information networks
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Ranking-based classification of heterogeneous information networks
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Construction and analysis of web-based computer science information networks
RSFDGrC'11 Proceedings of the 13th international conference on Rough sets, fuzzy sets, data mining and granular computing
Citation count prediction: learning to estimate future citations for literature
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PAV: A novel model for ranking heterogeneous objects in bibliographic information networks
Expert Systems with Applications: An International Journal
On truth discovery in social sensing: a maximum likelihood estimation approach
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Author name disambiguation for ranking and clustering pubmed data using netclus
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
Modeling and exploiting heterogeneous bibliographic networks for expertise ranking
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Mining heterogeneous information networks: the next frontier
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The missing models: a data-driven approach for learning how networks grow
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The contextual focused topic model
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Link Prediction in a Modified Heterogeneous Bibliographic Network
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Research-insight: providing insight on research by publication network analysis
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Mining heterogeneous information networks: a structural analysis approach
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Maximum likelihood analysis of conflicting observations in social sensing
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Heterogeneous graph-based intent learning with queries, web pages and Wikipedia concepts
Proceedings of the 7th ACM international conference on Web search and data mining
Learning latent representations of nodes for classifying in heterogeneous social networks
Proceedings of the 7th ACM international conference on Web search and data mining
Personalized entity recommendation: a heterogeneous information network approach
Proceedings of the 7th ACM international conference on Web search and data mining
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Interesting pattern mining in multi-relational data
Data Mining and Knowledge Discovery
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A heterogeneous information network is an information network composed of multiple types of objects. Clustering on such a network may lead to better understanding of both hidden structures of the network and the individual role played by every object in each cluster. However, although clustering on homogeneous networks has been studied over decades, clustering on heterogeneous networks has not been addressed until recently. A recent study proposed a new algorithm, RankClus, for clustering on bi-typed heterogeneous networks. However, a real-world network may consist of more than two types, and the interactions among multi-typed objects play a key role at disclosing the rich semantics that a network carries. In this paper, we study clustering of multi-typed heterogeneous networks with a star network schema and propose a novel algorithm, NetClus, that utilizes links across multityped objects to generate high-quality net-clusters. An iterative enhancement method is developed that leads to effective ranking-based clustering in such heterogeneous networks. Our experiments on DBLP data show that NetClus generates more accurate clustering results than the baseline topic model algorithm PLSA and the recently proposed algorithm, RankClus. Further, NetClus generates informative clusters, presenting good ranking and cluster membership information for each attribute object in each net-cluster.