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Author: Philip S. Yu
Publisher: Springer Science & Business Media
Published: 2010-09-16
Total Pages: 580
ISBN-13: 1441965157
DOWNLOAD EBOOKThis 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: Philip S. Yu
Publisher: Springer
Published: 2010-09-29
Total Pages: 586
ISBN-13: 9781441965141
DOWNLOAD EBOOKThis 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: François Fouss
Publisher: Cambridge University Press
Published: 2016-07-12
Total Pages: 549
ISBN-13: 1316712516
DOWNLOAD EBOOKNetwork 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.
Author: Jure Leskovec
Publisher: Cambridge University Press
Published: 2014-11-13
Total Pages: 480
ISBN-13: 1107077230
DOWNLOAD EBOOKNow in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.
Author: Álvaro Herrero
Publisher: Springer
Published: 2015-05-31
Total Pages: 471
ISBN-13: 3319197193
DOWNLOAD EBOOKThis volume of Advances in Intelligent and Soft Computing contains accepted papers presented at the 10th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2015), held in the beautiful and historic city of Burgos (Spain), in June 2015. Soft computing represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines, which investigate, simulate and analyze very complex issues and phenomena. This Conference is mainly focused on its industrial and environmental applications. After a through peer-review process, the SOCO 2015 International Program Committee selected 41 papers, written by authors from 15 different countries. These papers are published in present conference proceedings, achieving an acceptance rate of 40%. The selection of papers was extremely rigorous in order to maintain the high quality of the conference and we would like to thank the members of the International Program Committees for their hard work during the review process. This is a crucial issue for creation of a high standard conference and the SOCO conference would not exist without their help.
Author: Peter Christen
Publisher: Springer Science & Business Media
Published: 2012-07-04
Total Pages: 279
ISBN-13: 3642311644
DOWNLOAD EBOOKData matching (also known as record or data linkage, entity resolution, object identification, or field matching) is the task of identifying, matching and merging records that correspond to the same entities from several databases or even within one database. Based on research in various domains including applied statistics, health informatics, data mining, machine learning, artificial intelligence, database management, and digital libraries, significant advances have been achieved over the last decade in all aspects of the data matching process, especially on how to improve the accuracy of data matching, and its scalability to large databases. Peter Christen’s book is divided into three parts: Part I, “Overview”, introduces the subject by presenting several sample applications and their special challenges, as well as a general overview of a generic data matching process. Part II, “Steps of the Data Matching Process”, then details its main steps like pre-processing, indexing, field and record comparison, classification, and quality evaluation. Lastly, part III, “Further Topics”, deals with specific aspects like privacy, real-time matching, or matching unstructured data. Finally, it briefly describes the main features of many research and open source systems available today. By providing the reader with a broad range of data matching concepts and techniques and touching on all aspects of the data matching process, this book helps researchers as well as students specializing in data quality or data matching aspects to familiarize themselves with recent research advances and to identify open research challenges in the area of data matching. To this end, each chapter of the book includes a final section that provides pointers to further background and research material. Practitioners will better understand the current state of the art in data matching as well as the internal workings and limitations of current systems. Especially, they will learn that it is often not feasible to simply implement an existing off-the-shelf data matching system without substantial adaption and customization. Such practical considerations are discussed for each of the major steps in the data matching process.
Author: Vincenc Torra
Publisher: Springer
Published: 2012-11-07
Total Pages: 433
ISBN-13: 3642346200
DOWNLOAD EBOOKThis book constitutes the refereed proceedings of the 9th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2012, held in Girona, Catalonia, Spain, in November 2012. The 32 revised full papers were carefully reviewed and selected from 49 submissions and are presented with 4 plenary talks. The papers are organized in topical sections on aggregation operators, integrals, data privacy and security, reasoning, applications, and clustering and similarity.
Author: Eric Yu
Publisher: Springer
Published: 2014-10-10
Total Pages: 496
ISBN-13: 3319122061
DOWNLOAD EBOOKThis book constitutes the refereed proceedings of the 32nd International Conference on Conceptual Modeling, ER 2014, held in Atlanta, GA, USA. The 23 full and 15 short papers presented were carefully reviewed and selected from 80 submissions. Topics of interest presented and discussed in the conference span the entire spectrum of conceptual modeling including research and practice in areas such as: data on the web, unstructured data, uncertain and incomplete data, big data, graphs and networks, privacy and safety, database design, new modeling languages and applications, software concepts and strategies, patterns and narratives, data management for enterprise architecture, city and urban applications.
Author: Derek Doran
Publisher: Springer
Published: 2017-03-20
Total Pages: 109
ISBN-13: 3319538861
DOWNLOAD EBOOKThis brief presents readers with a summary of classic, modern, and state-of-the-art methods for discovering the roles of entities in networks (including social networks) that range from small to large-scale. It classifies methods by their mathematical underpinning, whether they are driven by implications about entity behaviors in system, or if they are purely data driven. The brief also discusses when and how each method should be applied, and discusses some outstanding challenges toward the development of future role mining methods of each type.
Author: Mohammed J. Zaki
Publisher: Cambridge University Press
Published: 2020-01-30
Total Pages: 779
ISBN-13: 1108473989
DOWNLOAD EBOOKNew to the second edition of this advanced text are several chapters on regression, including neural networks and deep learning.
