A multilevel algorithm for partitioning graphs
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Multilevel k-way partitioning scheme for irregular graphs
Journal of Parallel and Distributed Computing
Multiway partitioning with pairwise movement
Proceedings of the 1998 IEEE/ACM international conference on Computer-aided design
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
SIAM Journal on Scientific Computing
Authoritative sources in a hyperlinked environment
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Efficient identification of Web communities
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mesh Partitioning: A Multilevel Balancing and Refinement Algorithm
SIAM Journal on Scientific Computing
Reasoning for web document associations and its applications in site map construction
Data & Knowledge Engineering
Genetic Algorithm and Graph Partitioning
IEEE Transactions on Computers
On clusterings-good, bad and spectral
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
A linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
Improved approximation algorithms for minimum-weight vertex separators
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
Graph evolution: Densification and shrinking diameters
ACM Transactions on Knowledge Discovery from Data (TKDD)
Geometric crossovers for multiway graph partitioning
Evolutionary Computation
Statistical properties of community structure in large social and information networks
Proceedings of the 17th international conference on World Wide Web
Ranks and Representations for Spectral Graph Bisection
SIAM Journal on Scientific Computing
Data & Knowledge Engineering
Parallel Spectral Clustering in Distributed Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Document clustering using synthetic cluster prototypes
Data & Knowledge Engineering
IEEE Transactions on Parallel and Distributed Systems
Stock price movement prediction using representative prototypes of financial reports
ACM Transactions on Management Information Systems (TMIS)
A unique property of single-link distance and its application in data clustering
Data & Knowledge Engineering
Hierarchical community detection with applications to real-world network analysis
Data & Knowledge Engineering
Decomposing Petri nets for process mining: A generic approach
Distributed and Parallel Databases
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Graphs are used for modeling a large spectrum of data from the web, to social connections between individuals, to concept maps and ontologies. As the number and complexities of graph based applications increase, rendering these graphs more compact, easier to understand, and navigate through are becoming crucial tasks. One approach to graph simplification is to partition the graph into smaller parts, so that instead of the whole graph, the partitions and their inter-connections need to be considered. Common approaches to graph partitioning involve identifying sets of edges (or edge-cuts) or vertices (or vertex-cuts) whose removal partitions the graph into the target number of disconnected components. While edge-cuts result in partitions that are vertex disjoint, in vertex-cuts the data vertices can serve as bridges between the resulting data partitions; consequently, vertex-cut based approaches are especially suitable when the vertices on the vertex-cut will be replicated on all relevant partitions. A significant challenge in vertex-cut based partitioning, however, is ensuring the balance of the resulting partitions while simultaneously minimizing the number of vertices that are cut (and thus replicated). In this paper, we propose a SBV-Cut algorithm which identifies a set of balance vertices that can be used to effectively and efficiently bisect a directed graph. The graph can then be further partitioned by a recursive application of structurally-balanced cuts to obtain a hierarchical partitioning of the graph. Experiments show that SBV-Cut provides better vertex-cut based expansion and modularity scores than its competitors and works several orders more efficiently than constraint-minimization based approaches.