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The Application Of Clustering Techniques To Citation Data
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Book Synopsis The Application of Clustering Techniques to Citation Data by : University of Bath. Library
Download or read book The Application of Clustering Techniques to Citation Data written by University of Bath. Library and published by . This book was released on 1977 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Grouping Multidimensional Data by : Jacob Kogan
Download or read book Grouping Multidimensional Data written by Jacob Kogan and published by Taylor & Francis. This book was released on 2006-02-10 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher description
Book Synopsis Data Mining and Knowledge Discovery Handbook by : Oded Maimon
Download or read book Data Mining and Knowledge Discovery Handbook written by Oded Maimon and published by Springer Science & Business Media. This book was released on 2006-05-28 with total page 1378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.
Book Synopsis Data Clustering by : Charu C. Aggarwal
Download or read book Data Clustering written by Charu C. Aggarwal and published by CRC Press. This book was released on 2013-08-21 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains. The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validation In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain how to glean detailed insight from the clustering process—including how to verify the quality of the underlying clusters—through supervision, human intervention, or the automated generation of alternative clusters.
Book Synopsis Data Clustering: Theory, Algorithms, and Applications, Second Edition by : Guojun Gan
Download or read book Data Clustering: Theory, Algorithms, and Applications, Second Edition written by Guojun Gan and published by SIAM. This book was released on 2020-11-10 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments, covers the basics of data clustering, includes a list of popular clustering algorithms, and provides program code that helps users implement clustering algorithms. Data Clustering: Theory, Algorithms and Applications, Second Edition will be of interest to researchers, practitioners, and data scientists as well as undergraduate and graduate students.
Book Synopsis Clustering Algorithms by : John A. Hartigan
Download or read book Clustering Algorithms written by John A. Hartigan and published by John Wiley & Sons. This book was released on 1975 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Shows how Galileo, Newton, and Einstein tried to explain gravity. Discusses the concept of microgravity and NASA's research on gravity and microgravity.
Book Synopsis Model-Based Clustering and Classification for Data Science by : Charles Bouveyron
Download or read book Model-Based Clustering and Classification for Data Science written by Charles Bouveyron and published by Cambridge University Press. This book was released on 2019-07-25 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering. Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics.
Book Synopsis Mining Text Data by : Charu C. Aggarwal
Download or read book Mining Text Data written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2012-02-03 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.
Book Synopsis Recent Applications in Data Clustering by : Harun Pirim
Download or read book Recent Applications in Data Clustering written by Harun Pirim and published by BoD – Books on Demand. This book was released on 2018-08-01 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clustering has emerged as one of the more fertile fields within data analytics, widely adopted by companies, research institutions, and educational entities as a tool to describe similar/different groups. The book Recent Applications in Data Clustering aims to provide an outlook of recent contributions to the vast clustering literature that offers useful insights within the context of modern applications for professionals, academics, and students. The book spans the domains of clustering in image analysis, lexical analysis of texts, replacement of missing values in data, temporal clustering in smart cities, comparison of artificial neural network variations, graph theoretical approaches, spectral clustering, multiview clustering, and model-based clustering in an R package. Applications of image, text, face recognition, speech (synthetic and simulated), and smart city datasets are presented.
Book Synopsis Computational Science and Its Applications - ICCSA 2014 by : Beniamino Murgante
Download or read book Computational Science and Its Applications - ICCSA 2014 written by Beniamino Murgante and published by Springer. This book was released on 2014-07-02 with total page 840 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six-volume set LNCS 8579-8584 constitutes the refereed proceedings of the 14th International Conference on Computational Science and Its Applications, ICCSA 2014, held in Guimarães, Portugal, in June/July 2014. The 347 revised papers presented in 30 workshops and a special track were carefully reviewed and selected from 1167. The 289 papers presented in the workshops cover various areas in computational science ranging from computational science technologies to specific areas of computational science such as computational geometry and security.
Book Synopsis Measuring Scholarly Impact by : Ying Ding
Download or read book Measuring Scholarly Impact written by Ying Ding and published by Springer. This book was released on 2014-11-06 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an authoritative handbook of current topics, technologies and methodological approaches that may be used for the study of scholarly impact. The included methods cover a range of fields such as statistical sciences, scientific visualization, network analysis, text mining, and information retrieval. The techniques and tools enable researchers to investigate metric phenomena and to assess scholarly impact in new ways. Each chapter offers an introduction to the selected topic and outlines how the topic, technology or methodological approach may be applied to metrics-related research. Comprehensive and up-to-date, Measuring Scholarly Impact: Methods and Practice is designed for researchers and scholars interested in informetrics, scientometrics, and text mining. The hands-on perspective is also beneficial to advanced-level students in fields from computer science and statistics to information science.
Book Synopsis New Directions in Statistical Physics by : Luc T. Wille
Download or read book New Directions in Statistical Physics written by Luc T. Wille and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a unique insight into the latest breakthroughs in a consistent manner, at a level accessible to undergraduates, yet with enough attention to the theory and computation to satisfy the professional researcher Statistical physics addresses the study and understanding of systems with many degrees of freedom. As such it has a rich and varied history, with applications to thermodynamics, magnetic phase transitions, and order/disorder transformations, to name just a few. However, the tools of statistical physics can be profitably used to investigate any system with a large number of components. Thus, recent years have seen these methods applied in many unexpected directions, three of which are the main focus of this volume. These applications have been remarkably successful and have enriched the financial, biological, and engineering literature. Although reported in the physics literature, the results tend to be scattered and the underlying unity of the field overlooked.
Book Synopsis Data Clustering by : Charu C. Aggarwal
Download or read book Data Clustering written by Charu C. Aggarwal and published by CRC Press. This book was released on 2013-08-21 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains. The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validation In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain how to glean detailed insight from the clustering process—including how to verify the quality of the underlying clusters—through supervision, human intervention, or the automated generation of alternative clusters.
Book Synopsis Geodemographics, GIS and Neighbourhood Targeting by : Richard Harris
Download or read book Geodemographics, GIS and Neighbourhood Targeting written by Richard Harris and published by John Wiley & Sons. This book was released on 2005-12-13 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geodemographic classification is ‘big business’ in the marketing and service sector industries, and in public policy there has also been a resurgence of interest in neighbourhood initiatives and targeting. As an increasing number of professionals realise the potential of geographic analysis for their business or organisation, there exists a timely gap in the market for a focussed book on geodemographics and GIS. Geodemographics: neighbourhood targeting and GIS provides both an introduction to and overview of the methods, theory and classification techniques that provide the foundation of neighbourhood analysis and commercial geodemographic products. Particular focus is given to the presentation and use of neighbourhood classification in GIS. Authored by leading marketing professionals and a prominent academic, this book presents methods, theory and classification techniques in a reader-friendly manner Supported by private and public sector case studies and vignettes The applied ‘how to’ sections will specifically appeal to the intended audience at work in business and service planning Includes information on the recent UK and US Census products and resulting neighbourhood classifications
Book Synopsis Time Series Clustering and Classification by : Elizabeth Ann Maharaj
Download or read book Time Series Clustering and Classification written by Elizabeth Ann Maharaj and published by CRC Press. This book was released on 2019-03-19 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: The beginning of the age of artificial intelligence and machine learning has created new challenges and opportunities for data analysts, statisticians, mathematicians, econometricians, computer scientists and many others. At the root of these techniques are algorithms and methods for clustering and classifying different types of large datasets, including time series data. Time Series Clustering and Classification includes relevant developments on observation-based, feature-based and model-based traditional and fuzzy clustering methods, feature-based and model-based classification methods, and machine learning methods. It presents a broad and self-contained overview of techniques for both researchers and students. Features Provides an overview of the methods and applications of pattern recognition of time series Covers a wide range of techniques, including unsupervised and supervised approaches Includes a range of real examples from medicine, finance, environmental science, and more R and MATLAB code, and relevant data sets are available on a supplementary website
Book Synopsis Advances in Fuzzy Clustering and its Applications by : Jose Valente de Oliveira
Download or read book Advances in Fuzzy Clustering and its Applications written by Jose Valente de Oliveira and published by John Wiley & Sons. This book was released on 2007-06-13 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive, coherent, and in depth presentation of the state of the art in fuzzy clustering. Fuzzy clustering is now a mature and vibrant area of research with highly innovative advanced applications. Encapsulating this through presenting a careful selection of research contributions, this book addresses timely and relevant concepts and methods, whilst identifying major challenges and recent developments in the area. Split into five clear sections, Fundamentals, Visualization, Algorithms and Computational Aspects, Real-Time and Dynamic Clustering, and Applications and Case Studies, the book covers a wealth of novel, original and fully updated material, and in particular offers: a focus on the algorithmic and computational augmentations of fuzzy clustering and its effectiveness in handling high dimensional problems, distributed problem solving and uncertainty management. presentations of the important and relevant phases of cluster design, including the role of information granules, fuzzy sets in the realization of human-centricity facet of data analysis, as well as system modelling demonstrations of how the results facilitate further detailed development of models, and enhance interpretation aspects a carefully organized illustrative series of applications and case studies in which fuzzy clustering plays a pivotal role This book will be of key interest to engineers associated with fuzzy control, bioinformatics, data mining, image processing, and pattern recognition, while computer engineers, students and researchers, in most engineering disciplines, will find this an invaluable resource and research tool.
Book Synopsis Intelligent Multidimensional Data Clustering and Analysis by : Bhattacharyya, Siddhartha
Download or read book Intelligent Multidimensional Data Clustering and Analysis written by Bhattacharyya, Siddhartha and published by IGI Global. This book was released on 2016-11-29 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining analysis techniques have undergone significant developments in recent years. This has led to improved uses throughout numerous functions and applications. Intelligent Multidimensional Data Clustering and Analysis is an authoritative reference source for the latest scholarly research on the advantages and challenges presented by the use of cluster analysis techniques. Highlighting theoretical foundations, computing paradigms, and real-world applications, this book is ideally designed for researchers, practitioners, upper-level students, and professionals interested in the latest developments in cluster analysis for large data sets.