Modelling And Mining Networks

Author : Philip S. Yu
Publisher : Springer Science & Business Media
ISBN 13 : 1441965157
Total Pages : 580 pages
Book Rating : 4.58/5 ( download)

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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.

Author : Megan Dewar
Publisher : Springer Nature
ISBN 13 : 3031592050
Total Pages : 194 pages
Book Rating : 4.58/5 ( download)

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Download or read book Modelling and Mining Networks written by Megan Dewar and published by Springer Nature. This book was released on with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Bogumil Kaminski
Publisher : CRC Press
ISBN 13 : 1000515850
Total Pages : 278 pages
Book Rating : 4.55/5 ( download)

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Download or read book Mining Complex Networks written by Bogumil Kaminski and published by CRC Press. This book was released on 2021-12-15 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concentrates on mining networks, a subfield within data science. Data science uses scientific and computational tools to extract valuable knowledge from large data sets. Once data is processed and cleaned, it is analyzed and presented to support decision-making processes. Data science and machine learning tools have become widely used in companies of all sizes. Networks are often large-scale, decentralized, and evolve dynamically over time. Mining complex networks aim to understand the principles governing the organization and the behavior of such networks is crucial for a broad range of fields of study. Here are a few selected typical applications of mining networks: Community detection (which users on some social media platforms are close friends). Link prediction (who is likely to connect to whom on such platforms). Node attribute prediction (what advertisement should be shown to a given user of a particular platform to match their interests). Influential node detection (which social media users would be the best ambassadors of a specific product). This textbook is suitable for an upper-year undergraduate course or a graduate course in programs such as data science, mathematics, computer science, business, engineering, physics, statistics, and social science. This book can be successfully used by all enthusiasts of data science at various levels of sophistication to expand their knowledge or consider changing their career path. Jupiter notebooks (in Python and Julia) accompany the book and can be accessed on https://www.ryerson.ca/mining-complex-networks/. These not only contain all the experiments presented in the book, but also include additional material. Bogumił Kamiński is the Chairman of the Scientific Council for the Discipline of Economics and Finance at SGH Warsaw School of Economics. He is also an Adjunct Professor at the Data Science Laboratory at Ryerson University. Bogumił is an expert in applications of mathematical modeling to solving complex real-life problems. He is also a substantial open-source contributor to the development of the Julia language and its package ecosystem. Paweł Prałat is a Professor of Mathematics in Ryerson University, whose main research interests are in random graph theory, especially in modeling and mining complex networks. He is the Director of Fields-CQAM Lab on Computational Methods in Industrial Mathematics in The Fields Institute for Research in Mathematical Sciences and has pursued collaborations with various industry partners as well as the Government of Canada. He has written over 170 papers and three books with 130 plus collaborators. François Théberge holds a B.Sc. degree in applied mathematics from the University of Ottawa, a M.Sc. in telecommunications from INRS and a PhD in electrical engineering from McGill University. He has been employed by the Government of Canada since 1996 where he was involved in the creation of the data science team as well as the research group now known as the Tutte Institute for Mathematics and Computing. He also holds an adjunct professorial position in the Department of Mathematics and Statistics at the University of Ottawa. His current interests include relational-data mining and deep learning.

Author : Yizhou Sun
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1608458814
Total Pages : 161 pages
Book Rating : 4.13/5 ( download)

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Download or read book Mining Heterogeneous Information Networks written by Yizhou Sun and published by Morgan & Claypool Publishers. This book was released on 2012-08-15 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Real world physical and abstract data objects are interconnected, forming gigantic, interconnected networks. By structuring these data objects and interactions between these objects into multiple types, such networks become semi-structured heterogeneous information networks. Most real world applications that handle big data, including interconnected social media and social networks, scientific, engineering, or medical information systems, online e-commerce systems, and most database systems, can be structured into heterogeneous information networks. Therefore, effective analysis of large-scale heterogeneous information networks poses an interesting but critical challenge. In this monograph, we investigate the principles and methodologies of mining heterogeneous information networks. Departing from many existing network models that view data as homogeneous graphs or networks, our semi-structured heterogeneous information network model leverages the rich semantics of typed nodes and links in a network and uncovers surprisingly rich knowledge from interconnected data. This semi-structured heterogeneous network modeling leads to a series of new principles and powerful methodologies for mining interconnected data, including (1) rank-based clustering and classification, (2) meta-path-based similarity search and mining, (3) relation strength-aware mining, and many other potential developments. This monograph introduces this new research frontier and points out some promising research directions.

Author : Reda Alhajj
Publisher : Springer
ISBN 13 : 9781493971305
Total Pages : 0 pages
Book Rating : 4.01/5 ( download)

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Download or read book Encyclopedia of Social Network Analysis and Mining written by Reda Alhajj and published by Springer. This book was released on 2018-05-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Encyclopedia of Social Network Analysis and Mining (ESNAM) is the first major reference work to integrate fundamental concepts and research directions in the areas of social networks and applications to data mining. The second edition of ESNAM is a truly outstanding reference appealing to researchers, practitioners, instructors and students (both undergraduate and graduate), as well as the general public. This updated reference integrates all basics concepts and research efforts under one umbrella. Coverage has been expanded to include new emerging topics such as crowdsourcing, opinion mining, and sentiment analysis. Revised content of existing material keeps the encyclopedia current. The second edition is intended for college students as well as public and academic libraries. It is anticipated to continue to stimulate more awareness of social network applications and research efforts. The advent of electronic communication, and in particular on-line communities, have created social networks of hitherto unimaginable sizes. Reflecting the interdisciplinary nature of this unique field, the essential contributions of diverse disciplines, from computer science, mathematics, and statistics to sociology and behavioral science, are described among the 300 authoritative yet highly readable entries. Students will find a world of information and insight behind the familiar façade of the social networks in which they participate. Researchers and practitioners will benefit from a comprehensive perspective on the methodologies for analysis of constructed networks, and the data mining and machine learning techniques that have proved attractive for sophisticated knowledge discovery in complex applications. Also addressed is the application of social network methodologies to other domains, such as web networks and biological networks.

Author : Ding-Zhu Du
Publisher : Springer Science & Business Media
ISBN 13 : 0387238301
Total Pages : 395 pages
Book Rating : 4.02/5 ( download)

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Download or read book Handbook of Combinatorial Optimization written by Ding-Zhu Du and published by Springer Science & Business Media. This book was released on 2006-08-18 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a supplementary volume to the major three-volume Handbook of Combinatorial Optimization set. It can also be regarded as a stand-alone volume presenting chapters dealing with various aspects of the subject in a self-contained way.

Author : Jure Leskovec
Publisher : Cambridge University Press
ISBN 13 : 1107077230
Total Pages : 480 pages
Book Rating : 4.32/5 ( download)

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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.

Author : Nasrullah Memon
Publisher : Springer Science & Business Media
ISBN 13 : 1441962875
Total Pages : 217 pages
Book Rating : 4.74/5 ( download)

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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.

Author : Daniel T. Larose
Publisher : John Wiley & Sons
ISBN 13 : 0471756474
Total Pages : 340 pages
Book Rating : 4.77/5 ( download)

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Download or read book Data Mining Methods and Models written by Daniel T. Larose and published by John Wiley & Sons. This book was released on 2006-02-02 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apply powerful Data Mining Methods and Models to Leverage your Data for Actionable Results Data Mining Methods and Models provides: * The latest techniques for uncovering hidden nuggets of information * The insight into how the data mining algorithms actually work * The hands-on experience of performing data mining on large data sets Data Mining Methods and Models: * Applies a "white box" methodology, emphasizing an understanding of the model structures underlying the softwareWalks the reader through the various algorithms and provides examples of the operation of the algorithms on actual large data sets, including a detailed case study, "Modeling Response to Direct-Mail Marketing" * Tests the reader's level of understanding of the concepts and methodologies, with over 110 chapter exercises * Demonstrates the Clementine data mining software suite, WEKA open source data mining software, SPSS statistical software, and Minitab statistical software * Includes a companion Web site, www.dataminingconsultant.com, where the data sets used in the book may be downloaded, along with a comprehensive set of data mining resources. Faculty adopters of the book have access to an array of helpful resources, including solutions to all exercises, a PowerPoint(r) presentation of each chapter, sample data mining course projects and accompanying data sets, and multiple-choice chapter quizzes. With its emphasis on learning by doing, this is an excellent textbook for students in business, computer science, and statistics, as well as a problem-solving reference for data analysts and professionals in the field. An Instructor's Manual presenting detailed solutions to all the problems in the book is available onlne.

Author : Guandong Xu
Publisher : Springer Science & Business Media
ISBN 13 : 144197735X
Total Pages : 218 pages
Book Rating : 4.59/5 ( download)

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Download or read book Web Mining and Social Networking written by Guandong Xu and published by Springer Science & Business Media. This book was released on 2010-10-20 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the techniques and applications involved in the Web Mining, Web Personalization and Recommendation and Web Community Analysis domains, including a detailed presentation of the principles, developed algorithms, and systems of the research in these areas. The applications of web mining, and the issue of how to incorporate web mining into web personalization and recommendation systems are also reviewed. Additionally, the volume explores web community mining and analysis to find the structural, organizational and temporal developments of web communities and reveal the societal sense of individuals or communities. The volume will benefit both academic and industry communities interested in the techniques and applications of web search, web data management, web mining and web knowledge discovery, as well as web community and social network analysis.