Graph Based Data Mining On Social Networks

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Managing and Mining Graph Data

Author : Charu C. Aggarwal
Publisher : Springer Science & Business Media
ISBN 13 : 1441960457
Total Pages : 623 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Managing and Mining Graph Data by : Charu C. Aggarwal

Download or read book Managing and Mining Graph Data written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2010-02-02 with total page 623 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Graph Mining

Author : Deepayan Chakrabarti
Publisher : Morgan & Claypool Publishers
ISBN 13 : 160845116X
Total Pages : 209 pages
Book Rating : 4.6/5 (84 download)

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Book Synopsis Graph Mining by : Deepayan Chakrabarti

Download or read book Graph Mining written by Deepayan Chakrabarti and published by Morgan & Claypool Publishers. This book was released on 2012-10-01 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: What does the Web look like? How can we find patterns, communities, outliers, in a social network? Which are the most central nodes in a network? These are the questions that motivate this work. Networks and graphs appear in many diverse settings, for example in social networks, computer-communication networks (intrusion detection, traffic management), protein-protein interaction networks in biology, document-text bipartite graphs in text retrieval, person-account graphs in financial fraud detection, and others. In this work, first we list several surprising patterns that real graphs tend to follow. Then we give a detailed list of generators that try to mirror these patterns. Generators are important, because they can help with "what if" scenarios, extrapolations, and anonymization. Then we provide a list of powerful tools for graph analysis, and specifically spectral methods (Singular Value Decomposition (SVD)), tensors, and case studies like the famous "pageRank" algorithm and the "HITS" algorithm for ranking web search results. Finally, we conclude with a survey of tools and observations from related fields like sociology, which provide complementary viewpoints. Table of Contents: Introduction / Patterns in Static Graphs / Patterns in Evolving Graphs / Patterns in Weighted Graphs / Discussion: The Structure of Specific Graphs / Discussion: Power Laws and Deviations / Summary of Patterns / Graph Generators / Preferential Attachment and Variants / Incorporating Geographical Information / The RMat / Graph Generation by Kronecker Multiplication / Summary and Practitioner's Guide / SVD, Random Walks, and Tensors / Tensors / Community Detection / Influence/Virus Propagation and Immunization / Case Studies / Social Networks / Other Related Work / Conclusions

Social Network Data Analytics

Author : Charu C. Aggarwal
Publisher : Springer Science & Business Media
ISBN 13 : 1441984623
Total Pages : 508 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Social Network Data Analytics by : Charu C. Aggarwal

Download or read book Social Network Data Analytics written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2011-03-18 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Mining Graph Data

Author : Diane J. Cook
Publisher : John Wiley & Sons
ISBN 13 : 0470073039
Total Pages : 501 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Mining Graph Data by : Diane J. Cook

Download or read book Mining Graph Data written by Diane J. Cook and published by John Wiley & Sons. This book was released on 2006-12-18 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text takes a focused and comprehensive look at mining data represented as a graph, with the latest findings and applications in both theory and practice provided. Even if you have minimal background in analyzing graph data, with this book you’ll be able to represent data as graphs, extract patterns and concepts from the data, and apply the methodologies presented in the text to real datasets. There is a misprint with the link to the accompanying Web page for this book. For those readers who would like to experiment with the techniques found in this book or test their own ideas on graph data, the Web page for the book should be http://www.eecs.wsu.edu/MGD.

Practical Graph Mining with R

Author : Nagiza F. Samatova
Publisher : CRC Press
ISBN 13 : 1439860858
Total Pages : 495 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Practical Graph Mining with R by : Nagiza F. Samatova

Download or read book Practical Graph Mining with R written by Nagiza F. Samatova and published by CRC Press. This book was released on 2013-07-15 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover Novel and Insightful Knowledge from Data Represented as a GraphPractical Graph Mining with R presents a "do-it-yourself" approach to extracting interesting patterns from graph data. It covers many basic and advanced techniques for the identification of anomalous or frequently recurring patterns in a graph, the discovery of groups or cluste

Graph-Based Social Media Analysis

Author : Ioannis Pitas
Publisher : CRC Press
ISBN 13 : 1498719058
Total Pages : 436 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Graph-Based Social Media Analysis by : Ioannis Pitas

Download or read book Graph-Based Social Media Analysis written by Ioannis Pitas and published by CRC Press. This book was released on 2016-04-19 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focused on the mathematical foundations of social media analysis, Graph-Based Social Media Analysis provides a comprehensive introduction to the use of graph analysis in the study of social and digital media. It addresses an important scientific and technological challenge, namely the confluence of graph analysis and network theory with linear alge

Data Mining for Social Network Data

Author : Nasrullah Memon
Publisher : Springer Science & Business Media
ISBN 13 : 1441962875
Total Pages : 217 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Data Mining for Social Network Data by : Nasrullah Memon

Download or read book Data Mining for Social Network Data written by Nasrullah Memon and published by Springer Science & Business Media. This book was released on 2010-06-10 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Driven by counter-terrorism efforts, marketing analysis and an explosion in online social networking in recent years, data mining has moved to the forefront of information science. This proposed Special Issue on Data Mining for Social Network Data will present a broad range of recent studies in social networking analysis. It will focus on emerging trends and needs in discovery and analysis of communities, solitary and social activities, activities in open for a and commercial sites as well. It will also look at network modeling, infrastructure construction, dynamic growth and evolution pattern discovery using machine learning approaches and multi-agent based simulations. Editors are three rising stars in world of data mining, knowledge discovery, social network analysis, and information infrastructures, and are anchored by Springer author/editor Hsinchun Chen (Terrorism Informatics; Medical Informatics; Digital Government), who is one of the most prominent intelligence analysis and data mining experts in the world.

Link Mining: Models, Algorithms, and Applications

Author : Philip S. Yu
Publisher : Springer Science & Business Media
ISBN 13 : 1441965157
Total Pages : 580 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Link Mining: Models, Algorithms, and Applications by : Philip S. Yu

Download or read book Link Mining: Models, Algorithms, and Applications written by Philip S. Yu and published by Springer Science & Business Media. This book was released on 2010-09-16 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Mining of Massive Datasets

Author : Jure Leskovec
Publisher : Cambridge University Press
ISBN 13 : 1107077230
Total Pages : 480 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Mining of Massive Datasets by : Jure Leskovec

Download or read book Mining of Massive Datasets written by Jure Leskovec and published by Cambridge University Press. This book was released on 2014-11-13 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.

Netizens

Author : Michael Hauben
Publisher : Wiley-IEEE Computer Society Press
ISBN 13 :
Total Pages : 404 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Netizens by : Michael Hauben

Download or read book Netizens written by Michael Hauben and published by Wiley-IEEE Computer Society Press. This book was released on 1997-05-11 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors conducted online research to find out what makes the Internet "tick", resulting in this examination of the pioneering vision and actions that have helped make the Net possible. "Netizens" is a detailed description of the Net's construction and a step-by-step view of the past, present, and future of the Internet, the Usenet and the World Wide Web.

R and Data Mining

Author : Yanchang Zhao
Publisher : Academic Press
ISBN 13 : 012397271X
Total Pages : 251 pages
Book Rating : 4.1/5 (239 download)

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Book Synopsis R and Data Mining by : Yanchang Zhao

Download or read book R and Data Mining written by Yanchang Zhao and published by Academic Press. This book was released on 2012-12-31 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more.Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation.With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis. - Presents an introduction into using R for data mining applications, covering most popular data mining techniques - Provides code examples and data so that readers can easily learn the techniques - Features case studies in real-world applications to help readers apply the techniques in their work

Mining Complex Networks

Author : Bogumil Kaminski
Publisher : CRC Press
ISBN 13 : 9781032112053
Total Pages : 0 pages
Book Rating : 4.1/5 (12 download)

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Book Synopsis Mining Complex Networks by : Bogumil Kaminski

Download or read book Mining Complex Networks written by Bogumil Kaminski and published by CRC Press. This book was released on 2024-08-26 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concentrates on mining networks, a subfield within data science. Mining complex networks to understand the principles governing the organization and the behaviour of such networks is crucial for a broad range of fields of study.

Graph Data Mining

Author : Qi Xuan
Publisher : Springer Nature
ISBN 13 : 981162609X
Total Pages : 256 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Graph Data Mining by : Qi Xuan

Download or read book Graph Data Mining written by Qi Xuan and published by Springer Nature. This book was released on 2021-07-15 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph data is powerful, thanks to its ability to model arbitrary relationship between objects and is encountered in a range of real-world applications in fields such as bioinformatics, traffic network, scientific collaboration, world wide web and social networks. Graph data mining is used to discover useful information and knowledge from graph data. The complications of nodes, links and the semi-structure form present challenges in terms of the computation tasks, e.g., node classification, link prediction, and graph classification. In this context, various advanced techniques, including graph embedding and graph neural networks, have recently been proposed to improve the performance of graph data mining. This book provides a state-of-the-art review of graph data mining methods. It addresses a current hot topic – the security of graph data mining – and proposes a series of detection methods to identify adversarial samples in graph data. In addition, it introduces readers to graph augmentation and subgraph networks to further enhance the models, i.e., improve their accuracy and robustness. Lastly, the book describes the applications of these advanced techniques in various scenarios, such as traffic networks, social and technical networks, and blockchains.

Graph Theoretic Approaches for Analyzing Large-Scale Social Networks

Author : Meghanathan, Natarajan
Publisher : IGI Global
ISBN 13 : 1522528156
Total Pages : 376 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Graph Theoretic Approaches for Analyzing Large-Scale Social Networks by : Meghanathan, Natarajan

Download or read book Graph Theoretic Approaches for Analyzing Large-Scale Social Networks written by Meghanathan, Natarajan and published by IGI Global. This book was released on 2017-07-13 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social network analysis has created novel opportunities within the field of data science. The complexity of these networks requires new techniques to optimize the extraction of useful information. Graph Theoretic Approaches for Analyzing Large-Scale Social Networks is a pivotal reference source for the latest academic research on emerging algorithms and methods for the analysis of social networks. Highlighting a range of pertinent topics such as influence maximization, probabilistic exploration, and distributed memory, this book is ideally designed for academics, graduate students, professionals, and practitioners actively involved in the field of data science.

Graph-theoretic Techniques for Web Content Mining

Author : Adam Schenker
Publisher : World Scientific
ISBN 13 : 9812563393
Total Pages : 250 pages
Book Rating : 4.8/5 (125 download)

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Book Synopsis Graph-theoretic Techniques for Web Content Mining by : Adam Schenker

Download or read book Graph-theoretic Techniques for Web Content Mining written by Adam Schenker and published by World Scientific. This book was released on 2005 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes exciting new opportunities for utilizing robust graph representations of data with common machine learning algorithms. Graphs can model additional information which is often not present in commonly used data representations, such as vectors. Through the use of graph distance ? a relatively new approach for determining graph similarity ? the authors show how well-known algorithms, such as k-means clustering and k-nearest neighbors classification, can be easily extended to work with graphs instead of vectors. This allows for the utilization of additional information found in graph representations, while at the same time employing well-known, proven algorithms.To demonstrate and investigate these novel techniques, the authors have selected the domain of web content mining, which involves the clustering and classification of web documents based on their textual substance. Several methods of representing web document content by graphs are introduced; an interesting feature of these representations is that they allow for a polynomial time distance computation, something which is typically an NP-complete problem when using graphs. Experimental results are reported for both clustering and classification in three web document collections using a variety of graph representations, distance measures, and algorithm parameters.In addition, this book describes several other related topics, many of which provide excellent starting points for researchers and students interested in exploring this new area of machine learning further. These topics include creating graph-based multiple classifier ensembles through random node selection and visualization of graph-based data using multidimensional scaling.

Mining Heterogeneous Information Networks

Author : Yizhou Sun
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1608458806
Total Pages : 162 pages
Book Rating : 4.6/5 (84 download)

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Book Synopsis Mining Heterogeneous Information Networks by : Yizhou Sun

Download or read book Mining Heterogeneous Information Networks written by Yizhou Sun and published by Morgan & Claypool Publishers. This book was released on 2012 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Investigates the principles and methodologies of mining heterogeneous information networks. Departing from many existing network models that view interconnected data as homogeneous graphs or networks, the semi-structured heterogeneous information network model leverages the rich semantics of typed nodes and links in a network and uncovers surprisingly rich knowledge from the network.

Network Data Mining And Analysis

Author : Ming Gao
Publisher : World Scientific
ISBN 13 : 9813274972
Total Pages : 205 pages
Book Rating : 4.8/5 (132 download)

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Book Synopsis Network Data Mining And Analysis by : Ming Gao

Download or read book Network Data Mining And Analysis written by Ming Gao and published by World Scientific. This book was released on 2018-09-28 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Online social networking sites like Facebook, LinkedIn, and Twitter, offer millions of members the opportunity to befriend one another, send messages to each other, and post content on the site — actions which generate mind-boggling amounts of data every day.To make sense of the massive data from these sites, we resort to social media mining to answer questions like the following: