Relational Data Clustering

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Relational Data Clustering

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Author : Bo Long
language : en
Publisher: CRC Press
Release Date : 2010-05-19

Relational Data Clustering written by Bo Long and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-19 with Business & Economics categories.

A culmination of the authors' years of extensive research on this topic, Relational Data Clustering: Models, Algorithms, and Applications addresses the fundamentals and applications of relational data clustering. It describes theoretic models and algorithms and, through examples, shows how to apply these models and algorithms to solve real-world problems. After defining the field, the book introduces different types of model formulations for relational data clustering, presents various algorithms for the corresponding models, and demonstrates applications of the models and algorithms through extensive experimental results. The authors cover six topics of relational data clustering: Clustering on bi-type heterogeneous relational data Multi-type heterogeneous relational data Homogeneous relational data clustering Clustering on the most general case of relational data Individual relational clustering framework Recent research on evolutionary clustering This book focuses on both practical algorithm derivation and theoretical framework construction for relational data clustering. It provides a complete, self-contained introduction to advances in the field.

Artificial Intelligence And Computational Intelligence

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Author : Hepu Deng
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-09-12

Artificial Intelligence And Computational Intelligence written by Hepu Deng and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-12 with Computers categories.

This three-volume proceedings contains revised selected papers from the Second International Conference on Artificial Intelligence and Computational Intelligence, AICI 2011, held in Taiyuan, China, in September 2011. The total of 265 high-quality papers presented were carefully reviewed and selected from 1073 submissions. The topics of Part I covered are: applications of artificial intelligence; applications of computational intelligence; automated problem solving; biomedical inforamtics and computation; brain models/cognitive science; data mining and knowledge discovering; distributed AI and agents; evolutionary programming; expert and decision support systems; fuzzy computation; fuzzy logic and soft computing; and genetic algorithms.

Stochastic And Iterative Techniques For Relational Data Clustering

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Author : Adam P. Anthony
language : en
Publisher:
Release Date : 2009

Stochastic And Iterative Techniques For Relational Data Clustering written by Adam P. Anthony and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.

Link Mining Models Algorithms And Applications

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Author : Philip S. Yu
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-09-16

Link Mining Models Algorithms And Applications written by Philip S. Yu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-16 with Science categories.

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.

Advances In Fuzzy Clustering And Its Applications

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Author : Jose Valente de Oliveira
language : en
Publisher: John Wiley & Sons
Release Date : 2007-06-13

Advances In Fuzzy Clustering And Its Applications written by Jose Valente de Oliveira and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-13 with Technology & Engineering categories.

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.

Sql Server Big Data Clusters

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Author : Benjamin Weissman
language : en
Publisher: Apress
Release Date : 2019-11-26

Sql Server Big Data Clusters written by Benjamin Weissman and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-26 with Computers categories.

Get a head-start on learning one of SQL Server 2019’s latest and most impactful features—Big Data Clusters—that combines large volumes of non-relational data for analysis along with data stored relationally inside a SQL Server database. This book provides a first look at Big Data Clusters based upon SQL Server 2019 Release Candidate 1. Start now and get a jump on your competition in learning this important new feature. Big Data Clusters is a feature set covering data virtualization, distributed computing, and relational databases and provides a complete AI platform across the entire cluster environment. This book shows you how to deploy, manage, and use Big Data Clusters. For example, you will learn how to combine data stored on the HDFS file system together with data stored inside the SQL Server instances that make up the Big Data Cluster. Filled with clear examples and use cases, this book provides everything necessary to get started working with Big Data Clusters in SQL Server 2019 using Release Candidate 1. You will learn about the architectural foundations that are made up from Kubernetes, Spark, HDFS, and SQL Server on Linux. You then are shown how to configure and deploy Big Data Clusters in on-premises environments or in the cloud. Next, you are taught about querying. You will learn to write queries in Transact-SQL—taking advantage of skills you have honed for years—and with those queries you will be able to examine and analyze data from a wide variety of sources such as Apache Spark. Through the theoretical foundation provided in this book and easy-to-follow example scripts and notebooks, you will be ready to use and unveil the full potential of SQL Server 2019: combining different types of data spread across widely disparate sources into a single view that is useful for business intelligence and machine learning analysis. What You Will Learn Install, manage, and troubleshoot Big Data Clusters in cloud or on-premise environments Analyze large volumes of data directly from SQL Server and/or Apache Spark Manage data stored in HDFS from SQL Server as if it were relational data Implement advanced analytics solutions through machine learning and AI Expose different data sources as a single logical source using data virtualization Who This Book Is For For data engineers, data scientists, data architects, and database administrators who want to employ data virtualization and big data analytics in their environment

Clustering In Relational Data And Ontologies

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Author : Timothy C. Havens
language : en
Publisher:
Release Date : 2010

Clustering In Relational Data And Ontologies written by Timothy C. Havens and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Cluster analysis categories.

This dissertation studies the problem of clustering objects represented by relational data. This is a pertinent problem as many real-world data sets can only be represented by relational data for which object-based clustering algorithms are not designed. Relational data are encountered in many fields including biology, management, industrial engineering, and social sciences. Unlike numerical object data, which are represented by a set of feature values (e.g. height, weight, shoe size) of an object, relational object data are the numerical values of (dis) similarity between objects. For this reason, conventional cluster analysis methods such as k-means and fuzzy c-means cannot be used directly with relational data. I focus on three main problems of cluster analysis of relational data: (i) tendency prior to clustering -- how many clusters are there?; (ii) partitioning of objects -- which objects belong to which cluster?; and (iii) validity of the resultant clusters -- are the partitions \good"?Analyses are included in this dissertation that prove that the Visual Assessment of cluster Tendency (VAT) algorithm has a direct relation to single-linkage hierarchical clustering and Dunn's cluster validity index. These analyses are important to the development of two novel clustering algorithms, CLODD-CLustering in Ordered Dissimilarity Data and ReSL-Rectangular Single-Linkage clustering. Last, this dissertation addresses clustering in ontologies; examples include the Gene Ontology, the MeSH ontology, patient medical records, and web documents. I apply an extension to the Self-Organizing Map (SOM) to produce a new algorithm, the OSOM-Ontological Self-Organizing Map. OSOM provides visualization and linguistic summarization of ontology-based data.

Learning Relational Data Using Clustering Ensembles Techniques

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Author : Soo Fun Tan
language : en
Publisher:
Release Date : 2015

Learning Relational Data Using Clustering Ensembles Techniques written by Soo Fun Tan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Cluster analysis categories.

Fuzzy Systems Conference Fuzz 2000

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Author : IEEE Neural Networks Council
language : en
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
Release Date : 2000-05

Fuzzy Systems Conference Fuzz 2000 written by IEEE Neural Networks Council and has been published by Institute of Electrical & Electronics Engineers(IEEE) this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-05 with Science categories.

Applications And Science Of Computational Intelligence Iv

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Author : Kevin L. Priddy
language : en
Publisher: SPIE-International Society for Optical Engineering
Release Date : 2001

Applications And Science Of Computational Intelligence Iv written by Kevin L. Priddy and has been published by SPIE-International Society for Optical Engineering this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.