Graph Partitioning And Graph Clustering
Download Graph Partitioning And Graph Clustering full books in PDF, epub, and Kindle. Read online free Graph Partitioning And Graph Clustering ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author | : David A. Bader |
Publisher | : American Mathematical Soc. |
Total Pages | : 258 |
Release | : 2013-03-18 |
Genre | : Mathematics |
ISBN | : 0821890387 |
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.
Author | : K. Erciyes |
Publisher | : Springer Nature |
Total Pages | : 229 |
Release | : 2021-11-17 |
Genre | : Computers |
ISBN | : 3030878864 |
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.
Author | : Charu C. Aggarwal |
Publisher | : Springer Science & Business Media |
Total Pages | : 623 |
Release | : 2010-02-02 |
Genre | : Computers |
ISBN | : 1441960457 |
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.
Author | : Claude Sammut |
Publisher | : Springer Science & Business Media |
Total Pages | : 1061 |
Release | : 2011-03-28 |
Genre | : Computers |
ISBN | : 0387307680 |
This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.
Author | : Jean-Francois Boulicaut |
Publisher | : Springer Science & Business Media |
Total Pages | : 578 |
Release | : 2004-09-10 |
Genre | : Computers |
ISBN | : 3540231080 |
This book constitutes the refereed proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2004, held in Pisa, Italy, in September 2004 jointly with ECML 2004. The 39 revised full papers and 9 revised short papers presented together with abstracts of 5 invited talks were carefully reviewed and selected from 194 papers submitted to PKDD and 107 papers submitted to both, PKDD and ECML. The papers present a wealth of new results in knowledge discovery in databases and address all current issues in the area.
Author | : Richard K. Belew |
Publisher | : Cambridge University Press |
Total Pages | : 388 |
Release | : 2000 |
Genre | : Computers |
ISBN | : 9780521630283 |
Explains how to build useful tools for searching collections of text and other media.
Author | : Lasse Kliemann |
Publisher | : Springer |
Total Pages | : 428 |
Release | : 2016-11-10 |
Genre | : Computers |
ISBN | : 3319494872 |
Algorithm Engineering is a methodology for algorithmic research that combines theory with implementation and experimentation in order to obtain better algorithms with high practical impact. Traditionally, the study of algorithms was dominated by mathematical (worst-case) analysis. In Algorithm Engineering, algorithms are also implemented and experiments conducted in a systematic way, sometimes resembling the experimentation processes known from fields such as biology, chemistry, or physics. This helps in counteracting an otherwise growing gap between theory and practice.
Author | : Ágnes Vathy-Fogarassy |
Publisher | : Springer Science & Business Media |
Total Pages | : 120 |
Release | : 2013-05-24 |
Genre | : Computers |
ISBN | : 1447151585 |
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.
Author | : Fan R. K. Chung |
Publisher | : American Mathematical Soc. |
Total Pages | : 228 |
Release | : |
Genre | : Mathematics |
ISBN | : 9780821889367 |
Beautifully written and elegantly presented, this book is based on 10 lectures given at the CBMS workshop on spectral graph theory in June 1994 at Fresno State University. Chung's well-written exposition can be likened to a conversation with a good teacher - one who not only gives you the facts, but tells you what is really going on, why it is worth doing, and how it is related to familiar ideas in other areas. The monograph is accessible to the nonexpert who is interested in reading about this evolving area of mathematics.
Author | : Hillol Kargupta |
Publisher | : SIAM |
Total Pages | : 670 |
Release | : 2005-04-01 |
Genre | : Mathematics |
ISBN | : 9780898715934 |
The Fifth SIAM International Conference on Data Mining continues the tradition of providing an open forum for the presentation and discussion of innovative algorithms as well as novel applications of data mining. Advances in information technology and data collection methods have led to the availability of large data sets in commercial enterprises and in a wide variety of scientific and engineering disciplines. The field of data mining draws upon extensive work in areas such as statistics, machine learning, pattern recognition, databases, and high performance computing to discover interesting and previously unknown information in data. This conference results in data mining, including applications, algorithms, software, and systems.