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Algorithms and Models for Network Data and Link Analysis

Algorithms and Models for Network Data and Link Analysis
Author: François Fouss
Publisher:
Total Pages: 521
Release: 2016
Genre: Network analysis (Planning)
ISBN: 9781107564817

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Network data are produced automatically by everyday interactions - social networks, power grids, and links between data sets are a few examples. Such data capture social and economic behavior in a form that can be analyzed using powerful computational tools. This book is a guide to both basic and advanced techniques and algorithms for extracting useful information from network data. The content is organized around 'tasks', grouping the algorithms needed to gather specific types of information and thus answer specific types of questions. Examples include similarity between nodes in a network, prestige or centrality of individual nodes, and dense regions or communities in a network. Algorithms are derived in detail and summarized in pseudo-code. The book is intended primarily for computer scientists, engineers, statisticians and physicists, but it is also accessible to network scientists based in the social sciences. Matlab/Octave code illustrating some of the algorithms will be available at: http://www.cambridge.org/9781107125773.


Algorithms and Models for Network Data and Link Analysis

Algorithms and Models for Network Data and Link Analysis
Author: François Fouss
Publisher: Cambridge University Press
Total Pages: 549
Release: 2016-07-12
Genre: Computers
ISBN: 1316712516

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Network data are produced automatically by everyday interactions - social networks, power grids, and links between data sets are a few examples. Such data capture social and economic behavior in a form that can be analyzed using powerful computational tools. This book is a guide to both basic and advanced techniques and algorithms for extracting useful information from network data. The content is organized around 'tasks', grouping the algorithms needed to gather specific types of information and thus answer specific types of questions. Examples include similarity between nodes in a network, prestige or centrality of individual nodes, and dense regions or communities in a network. Algorithms are derived in detail and summarized in pseudo-code. The book is intended primarily for computer scientists, engineers, statisticians and physicists, but it is also accessible to network scientists based in the social sciences. MATLAB®/Octave code illustrating some of the algorithms will be available at: http://www.cambridge.org/9781107125773.


Link Mining: Models, Algorithms, and Applications

Link Mining: Models, Algorithms, and Applications
Author: Philip S. Yu
Publisher: Springer Science & Business Media
Total Pages: 580
Release: 2010-09-16
Genre: Science
ISBN: 1441965157

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This book offers detailed surveys and systematic discussion of models, algorithms and applications for link mining, focusing on theory and technique, and related applications: text mining, social network analysis, collaborative filtering and bioinformatics.


Network Algorithms, Data Mining, and Applications

Network Algorithms, Data Mining, and Applications
Author: Ilya Bychkov
Publisher: Springer Nature
Total Pages: 251
Release: 2020-02-22
Genre: Mathematics
ISBN: 3030371573

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This proceedings presents the result of the 8th International Conference in Network Analysis, held at the Higher School of Economics, Moscow, in May 2018. The conference brought together scientists, engineers, and researchers from academia, industry, and government. Contributions in this book focus on the development of network algorithms for data mining and its applications. Researchers and students in mathematics, economics, statistics, computer science, and engineering find this collection a valuable resource filled with the latest research in network analysis. Computational aspects and applications of large-scale networks in market models, neural networks, social networks, power transmission grids, maximum clique problem, telecommunication networks, and complexity graphs are included with new tools for efficient network analysis of large-scale networks. Machine learning techniques in network settings including community detection, clustering, and biclustering algorithms are presented with applications to social network analysis.


Link Mining: Models, Algorithms, and Applications

Link Mining: Models, Algorithms, and Applications
Author: Philip S. Yu
Publisher: Springer
Total Pages: 586
Release: 2010-09-29
Genre: Science
ISBN: 9781441965141

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This book offers detailed surveys and systematic discussion of models, algorithms and applications for link mining, focusing on theory and technique, and related applications: text mining, social network analysis, collaborative filtering and bioinformatics.


Statistical Network Analysis: Models, Issues, and New Directions

Statistical Network Analysis: Models, Issues, and New Directions
Author: Edoardo M. Airoldi
Publisher: Springer
Total Pages: 200
Release: 2008-04-12
Genre: Computers
ISBN: 3540731334

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This book constitutes the thoroughly refereed post-proceedings of the International Workshop on Statistical Network Analysis: Models, Issues, and New Directions held in Pittsburgh, PA, USA in June 2006 as associated event of the 23rd International Conference on Machine Learning, ICML 2006. It covers probabilistic methods for network analysis, paying special attention to model design and computational issues of learning and inference.


Data Structures and Network Algorithms

Data Structures and Network Algorithms
Author: Robert Endre Tarjan
Publisher: SIAM
Total Pages: 138
Release: 1983-01-01
Genre: Technology & Engineering
ISBN: 9781611970265

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There has been an explosive growth in the field of combinatorial algorithms. These algorithms depend not only on results in combinatorics and especially in graph theory, but also on the development of new data structures and new techniques for analyzing algorithms. Four classical problems in network optimization are covered in detail, including a development of the data structures they use and an analysis of their running time. Data Structures and Network Algorithms attempts to provide the reader with both a practical understanding of the algorithms, described to facilitate their easy implementation, and an appreciation of the depth and beauty of the field of graph algorithms.


Social Network Data Analytics

Social Network Data Analytics
Author: Charu C. Aggarwal
Publisher: Springer Science & Business Media
Total Pages: 508
Release: 2011-03-18
Genre: Computers
ISBN: 1441984623

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Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Properties of Social Networks, Algorithms for Structural Discovery of Social Networks and Content Analysis in Social Networks. This book is also unique in focussing on the data analytical aspects of social networks in the internet scenario, rather than the traditional sociology-driven emphasis prevalent in the existing books, which do not focus on the unique data-intensive characteristics of online social networks. Emphasis is placed on simplifying the content so that students and practitioners benefit from this book. This book targets advanced level students and researchers concentrating on computer science as a secondary text or reference book. Data mining, database, information security, electronic commerce and machine learning professionals will find this book a valuable asset, as well as primary associations such as ACM, IEEE and Management Science.


Models and Methods in Social Network Analysis

Models and Methods in Social Network Analysis
Author: Peter J. Carrington
Publisher: Cambridge University Press
Total Pages: 354
Release: 2005-02-07
Genre: Social Science
ISBN: 9781139443432

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Models and Methods in Social Network Analysis, first published in 2005, presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s. Intended as a complement to Wasserman and Faust's Social Network Analysis: Methods and Applications, it is a collection of articles by leading methodologists reviewing advances in their particular areas of network methods. Reviewed are advances in network measurement, network sampling, the analysis of centrality, positional analysis or blockmodelling, the analysis of diffusion through networks, the analysis of affiliation or 'two-mode' networks, the theory of random graphs, dependence graphs, exponential families of random graphs, the analysis of longitudinal network data, graphical techniques for exploring network data, and software for the analysis of social networks.


A-Z of Digital Research Methods

A-Z of Digital Research Methods
Author: Catherine Dawson
Publisher: Routledge
Total Pages: 378
Release: 2019-07-10
Genre: Science
ISBN: 1351044656

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This accessible, alphabetical guide provides concise insights into a variety of digital research methods, incorporating introductory knowledge with practical application and further research implications. A-Z of Digital Research Methods provides a pathway through the often-confusing digital research landscape, while also addressing theoretical, ethical and legal issues that may accompany each methodology. Dawson outlines 60 chapters on a wide range of qualitative and quantitative digital research methods, including textual, numerical, geographical and audio-visual methods. This book includes reflection questions, useful resources and key texts to encourage readers to fully engage with the methods and build a competent understanding of the benefits, disadvantages and appropriate usages of each method. A-Z of Digital Research Methods is the perfect introduction for any student or researcher interested in digital research methods for social and computer sciences.