Spectral K-way ratio-cut partitioning and clustering
DAC '93 Proceedings of the 30th international Design Automation Conference
A multilevel algorithm for partitioning graphs
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Fast algorithms for projected clustering
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
SIAM Journal on Scientific Computing
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Co-clustering documents and words using bipartite spectral graph partitioning
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Bipartite graph partitioning and data clustering
Proceedings of the tenth international conference on Information and knowledge management
A Min-max Cut Algorithm for Graph Partitioning and Data Clustering
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Latent Class Models for Collaborative Filtering
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
A Unified Framework for Clustering Heterogeneous Web Objects
WISE '02 Proceedings of the 3rd International Conference on Web Information Systems Engineering
Cluster ensembles: a knowledge reuse framework for combining partitionings
Eighteenth national conference on Artificial intelligence
ReCoM: reinforcement clustering of multi-type interrelated data objects
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Generative model-based clustering of directional data
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Information-theoretic co-clustering
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
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A general model for clustering binary data
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Co-clustering by block value decomposition
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Spectral clustering for multi-type relational data
ICML '06 Proceedings of the 23rd international conference on Machine learning
Clustering with Bregman Divergences
The Journal of Machine Learning Research
Predictive discrete latent factor models for large scale dyadic data
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
A probabilistic framework for relational clustering
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Shine: search heterogeneous interrelated entities
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Compositional mining of multirelational biological datasets
ACM Transactions on Knowledge Discovery from Data (TKDD)
Proceedings of the 17th international conference on World Wide Web
Knowledge transformation from word space to document space
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
A Unified View of Matrix Factorization Models
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Quantify music artist similarity based on style and mood
Proceedings of the 10th ACM workshop on Web information and data management
Graph partitioning based on link distributions
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Learning semantic distance from community-tagged media collection
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Beyond the stars: exploiting free-text user reviews to improve the accuracy of movie recommendations
Proceedings of the 1st international CIKM workshop on Topic-sentiment analysis for mass opinion
Unifying dependent clustering and disparate clustering for non-homogeneous data
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Topic discovery of web video using star-structured K-partite graph
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Integrating Document Clustering and Multidocument Summarization
ACM Transactions on Knowledge Discovery from Data (TKDD)
A game theoretic framework for heterogenous information network clustering
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Detection of communities and bridges in weighted networks
MLDM'11 Proceedings of the 7th international conference on Machine learning and data mining in pattern recognition
Pattern change discovery between high dimensional data sets
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Discovering multirelational structure in social media streams
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
A unified framework for web video topic discovery and visualization
Pattern Recognition Letters
Subgraph mining on directed and weighted graphs
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Bayesian fuzzy clustering of colored graphs
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
Fast nonnegative matrix tri-factorization for large-scale data co-clustering
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Detecting communities in K-partite K-uniform (hyper)networks
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Summarization-based mining bipartite graphs
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Social event detection with robust high-order co-clustering
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Understanding evolving group structures in time-varying networks
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Social Link Prediction in Online Social Tagging Systems
ACM Transactions on Information Systems (TOIS)
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Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the research on mining the hidden structures from a k-partite graph is still limited and preliminary. In this paper, we propose a general model, the relation summary network, to find the hidden structures (the local cluster structures and the global community structures) from a k-partite graph. The model provides a principal framework for unsupervised learning on k-partite graphs of various structures. Under this model, we derive a novel algorithm to identify the hidden structures of a k-partite graph by constructing a relation summary network to approximate the original k-partite graph under a broad range of distortion measures. Experiments on both synthetic and real datasets demonstrate the promise and effectiveness of the proposed model and algorithm. We also establish the connections between existing clustering approaches and the proposed model to provide a unified view to the clustering approaches.