Algorithms for clustering data
Algorithms for clustering data
The electrical resistance of a graph captures its commute and cover times
STOC '89 Proceedings of the twenty-first annual ACM symposium on Theory of computing
Partitioning sparse matrices with eigenvectors of graphs
SIAM Journal on Matrix Analysis and Applications
Lexical analysis and stoplists
Information retrieval
Elements of information theory
Elements of information theory
Laplace eigenvalues of graphs—a survey
Discrete Mathematics - Algebraic graph theory; a volume dedicated to Gert Sabidussi
On the Optimality of the Median Cut Spectral Bisection Graph Partitioning Method
SIAM Journal on Scientific Computing
Drawing graphs to convey proximity: an incremental arrangement method
ACM Transactions on Computer-Human Interaction (TOCHI)
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Spectral partitioning with multiple eigenvectors
Discrete Applied Mathematics - Special volume on VLSI
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Concept decompositions for large sparse text data using clustering
Machine Learning
Spanning Forests of a Digraph and Their Applications
Automation and Remote Control
Automating the Construction of Internet Portals with Machine Learning
Information Retrieval
Diffusion Kernels on Graphs and Other Discrete Input Spaces
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
A Min-max Cut Algorithm for Graph Partitioning and Data Clustering
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Laplacian Eigenmaps for dimensionality reduction and data representation
Neural Computation
Segmentation Using Eigenvectors: A Unifying View
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Fuzzy C-Means Clustering Algorithm Based on Kernel Method
ICCIMA '03 Proceedings of the 5th International Conference on Computational Intelligence and Multimedia Applications
The Journal of Machine Learning Research
Efficient svm training using low-rank kernel representations
The Journal of Machine Learning Research
Towards a robust fuzzy clustering
Fuzzy Sets and Systems - Data analysis
Algorithms for estimating relative importance in networks
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Hierarchical model-based clustering of large datasets through fractionation and refractionation
Information Systems - Knowledge discovery and data mining (KDD 2002)
On clusterings: Good, bad and spectral
Journal of the ACM (JACM)
Clustering Large Graphs via the Singular Value Decomposition
Machine Learning
Cyclic pattern kernels for predictive graph mining
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Automatic multimedia cross-modal correlation discovery
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Linearized cluster assignment via spectral ordering
ICML '04 Proceedings of the twenty-first international conference on Machine learning
A kernel view of the dimensionality reduction of manifolds
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Mining Graph Data
A Novel Kernel Method for Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Application of kernels to link analysis
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Learning from labeled and unlabeled data on a directed graph
ICML '05 Proceedings of the 22nd international conference on Machine learning
Isoperimetric Partitioning: A New Algorithm for Graph Partitioning
SIAM Journal on Scientific Computing
Indexed-based density biased sampling for clustering applications
Data & Knowledge Engineering
Measuring and extracting proximity in networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
IEEE Transactions on Pattern Analysis and Machine Intelligence
Random Walks for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Experimental Investigation of Graph Kernels on a Collaborative Recommendation Task
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Pattern Recognition, Third Edition
Pattern Recognition, Third Edition
Node similarity in the citation graph
Knowledge and Information Systems
A robust deterministic annealing algorithm for data clustering
Data & Knowledge Engineering
The link-prediction problem for social networks
Journal of the American Society for Information Science and Technology
Classification in Networked Data: A Toolkit and a Univariate Case Study
The Journal of Machine Learning Research
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
A survey of kernel and spectral methods for clustering
Pattern Recognition
A tutorial on spectral clustering
Statistics and Computing
Clustering and Embedding Using Commute Times
IEEE Transactions on Pattern Analysis and Machine Intelligence
Random walk with restart: fast solutions and applications
Knowledge and Information Systems
Introduction to Information Retrieval
Introduction to Information Retrieval
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Cluster Analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Electricity based external similarity of categorical attributes
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
Graph nodes clustering based on the commute-time kernel
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Robust kernel fuzzy clustering
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
A novel kernelized fuzzy C-means algorithm with application in medical image segmentation
Artificial Intelligence in Medicine
Computer Science Review
Multilevel spectral hypergraph partitioning with arbitrary vertex sizes
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Mercer kernel-based clustering in feature space
IEEE Transactions on Neural Networks
Editorial: New fuzzy c-means clustering model based on the data weighted approach
Data & Knowledge Engineering
Link prediction: the power of maximal entropy random walk
Proceedings of the 20th ACM international conference on Information and knowledge management
MM '11 Proceedings of the 19th ACM international conference on Multimedia
A link-analysis-based discriminant analysis for exploring partially labeled graphs
Pattern Recognition Letters
An architecture to efficiently learn co-similarities from multi-view datasets
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part I
A new proposal for graph classification using frequent geometric subgraphs
Data & Knowledge Engineering
From biological to social networks: Link prediction based on multi-way spectral clustering
Data & Knowledge Engineering
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This work addresses the problem of detecting clusters in a weighted, undirected, graph by using kernel-based clustering methods, directly partitioning the graph according to a well-defined similarity measure between the nodes (a kernel on a graph). The proposed algorithms are based on a two-step procedure. First, a kernel or similarity matrix, providing a meaningful similarity measure between any couple of nodes, is computed from the adjacency matrix of the graph. Then, the nodes of the graph are clustered by performing a kernel clustering on this similarity matrix. Besides the introduction of a prototype-based kernel version of the gaussian mixtures model and Ward's hierarchical clustering, in addition to the already known kernel k-means and fuzzy k-means, a new kernel, called the sigmoid commute-time kernel (K"C"T^S) is presented. The joint use of the K"C"T^S kernel matrix and kernel clustering appears to be quite effective. Indeed, this methodology provides the best results on a systematic comparison with a selection of graph clustering and communities detection algorithms on three real-world databases. Finally, some links between the proposed hierarchical kernel clustering and spectral clustering are examined.