Graph Partitioning And Graph Clustering
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Graph Partitioning And Graph Clustering
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Author : David A. Bader
language : en
Publisher: American Mathematical Soc.
Release Date : 2013-03-18
Graph Partitioning And Graph Clustering written by David A. Bader and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-18 with Mathematics categories.
Graph partitioning and graph clustering are ubiquitous subtasks in many applications where graphs play an important role. Generally speaking, both techniques aim at the identification of vertex subsets with many internal and few external edges. To name only a few, problems addressed by graph partitioning and graph clustering algorithms are: What are the communities within an (online) social network? How do I speed up a numerical simulation by mapping it efficiently onto a parallel computer? How must components be organized on a computer chip such that they can communicate efficiently with each other? What are the segments of a digital image? Which functions are certain genes (most likely) responsible for? The 10th DIMACS Implementation Challenge Workshop was devoted to determining realistic performance of algorithms where worst case analysis is overly pessimistic and probabilistic models are too unrealistic. Articles in the volume describe and analyze various experimental data with the goal of getting insight into realistic algorithm performance in situations where analysis fails.
Algebraic Graph Algorithms
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Author : K. Erciyes
language : en
Publisher: Springer Nature
Release Date : 2021-11-17
Algebraic Graph Algorithms written by K. Erciyes and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-17 with Computers categories.
This textbook discusses the design and implementation of basic algebraic graph algorithms, and algebraic graph algorithms for complex networks, employing matroids whenever possible. The text describes the design of a simple parallel matrix algorithm kernel that can be used for parallel processing of algebraic graph algorithms. Example code is presented in pseudocode, together with case studies in Python and MPI. The text assumes readers have a background in graph theory and/or graph algorithms.
Graph Partitioning
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Author : Charles-Edmond Bichot
language : en
Publisher: John Wiley & Sons
Release Date : 2013-01-24
Graph Partitioning written by Charles-Edmond Bichot and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-24 with Computers categories.
Graph partitioning is a theoretical subject with applications in many areas, principally: numerical analysis, programs mapping onto parallel architectures, image segmentation, VLSI design. During the last 40 years, the literature has strongly increased and big improvements have been made. This book brings together the knowledge accumulated during many years to extract both theoretical foundations of graph partitioning and its main applications.
Data Clustering
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Author : Charu C. Aggarwal
language : en
Publisher: CRC Press
Release Date : 2018-09-03
Data Clustering written by Charu C. Aggarwal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-03 with Business & Economics categories.
Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains. The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validation In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain how to glean detailed insight from the clustering process—including how to verify the quality of the underlying clusters—through supervision, human intervention, or the automated generation of alternative clusters.
Graph Based Clustering And Data Visualization Algorithms
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Author : Ágnes Vathy-Fogarassy
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-05-24
Graph Based Clustering And Data Visualization Algorithms written by Ágnes Vathy-Fogarassy and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-24 with Computers categories.
This work presents a data visualization technique that combines graph-based topology representation and dimensionality reduction methods to visualize the intrinsic data structure in a low-dimensional vector space. The application of graphs in clustering and visualization has several advantages. A graph of important edges (where edges characterize relations and weights represent similarities or distances) provides a compact representation of the entire complex data set. This text describes clustering and visualization methods that are able to utilize information hidden in these graphs, based on the synergistic combination of clustering, graph-theory, neural networks, data visualization, dimensionality reduction, fuzzy methods, and topology learning. The work contains numerous examples to aid in the understanding and implementation of the proposed algorithms, supported by a MATLAB toolbox available at an associated website.
Managing And Mining Graph Data
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Author : Charu C. Aggarwal
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-02-02
Managing And Mining Graph Data written by Charu C. Aggarwal and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-02 with Computers categories.
Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety of important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy. It also studies a number of domain-specific scenarios such as stream mining, web graphs, social networks, chemical and biological data. The chapters are written by well known researchers in the field, and provide a broad perspective of the area. This is the first comprehensive survey book in the emerging topic of graph data processing. Managing and Mining Graph Data is designed for a varied audience composed of professors, researchers and practitioners in industry. This volume is also suitable as a reference book for advanced-level database students in computer science and engineering.
Relational Data Clustering
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Author : Bo Long
language : en
Publisher: CRC Press
Release Date : 2010-05-19
Relational Data Clustering written by Bo Long and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-19 with Business & Economics categories.
A culmination of the authors' years of extensive research on this topic, Relational Data Clustering: Models, Algorithms, and Applications addresses the fundamentals and applications of relational data clustering. It describes theoretic models and algorithms and, through examples, shows how to apply these models and algorithms to solve real-world problems. After defining the field, the book introduces different types of model formulations for relational data clustering, presents various algorithms for the corresponding models, and demonstrates applications of the models and algorithms through extensive experimental results. The authors cover six topics of relational data clustering: Clustering on bi-type heterogeneous relational data Multi-type heterogeneous relational data Homogeneous relational data clustering Clustering on the most general case of relational data Individual relational clustering framework Recent research on evolutionary clustering This book focuses on both practical algorithm derivation and theoretical framework construction for relational data clustering. It provides a complete, self-contained introduction to advances in the field.
Algorithms Esa 2003
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Author : Giuseppe Di Battista
language : en
Publisher: Springer
Release Date : 2003-10-02
Algorithms Esa 2003 written by Giuseppe Di Battista and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-10-02 with Computers categories.
This book constitutes the refereed proceedings of the 11th Annual European Symposium on Algorithms, ESA 2003, held in Budapest, Hungary, in September 2003. The 66 revised full papers presented were carefully reviewed and selected from 165 submissions. The scope of the papers spans the entire range of algorithmics from design and mathematical analysis issues to real-world applications, engineering, and experimental analysis of algorithms.
Optimal Graph Clustering Problems With Applications To Information System Design Partitioning Database
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Author : Wan Ping Chiang
language : en
Publisher:
Release Date : 1984
Optimal Graph Clustering Problems With Applications To Information System Design Partitioning Database written by Wan Ping Chiang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with Cluster analysis categories.
software) design problems.
Grouping Multidimensional Data
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Author : Jacob Kogan
language : en
Publisher: Taylor & Francis
Release Date : 2006-02-10
Grouping Multidimensional Data written by Jacob Kogan and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-02-10 with Computers categories.
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