Автор: Thomas Villmann; M. Biehl; Barbara Hammer; Michel Название: Similarity-Based Clustering ISBN: 3642018041 ISBN-13(EAN): 9783642018046 Издательство: Springer Рейтинг: Цена: 95770.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Recent Developments and Biomedical Applications. .
Автор: Philip D. Waggoner Название: Unsupervised Machine Learning for Clustering in Political and Social Research ISBN: 110879338X ISBN-13(EAN): 9781108793384 Издательство: Cambridge Academ Рейтинг: Цена: 19010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Offers researchers and teachers an introduction to clustering, which is a prominent class of unsupervised machine learning for exploring and understanding latent, non-random structure in data. A suite of widely used clustering techniques is covered, in addition to R code and real data to facilitate interaction with the concepts.
Автор: Olfa Nasraoui; Chiheb-Eddine Ben N`Cir Название: Clustering Methods for Big Data Analytics ISBN: 3319978632 ISBN-13(EAN): 9783319978635 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems. The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of data; clustering Big Data Streams such as streams generated by the confluence of Internet of Things, digital and mobile health, human-robot interaction, and social networks; Spark-based Big Data clustering using Particle Swarm Optimization; and Tensor-based clustering for Web graphs, sensor streams, and social networks. The chapters in the book include a balanced coverage of big data clustering theory, methods, tools, frameworks, applications, representation, visualization, and clustering validation.
Автор: Seetha Hari, Murty M. Narasimha, Tripathy B. K. Название: Modern Technologies for Big Data Classification and Clustering ISBN: 1522528059 ISBN-13(EAN): 9781522528050 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 208830.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Data has increased due to the growing use of web applications and communication devices. It is necessary to develop new techniques of managing data in order to ensure adequate usage.Modern Technologies for Big Data Classification and Clustering is an essential reference source for the latest scholarly research on handling large data sets with conventional data mining and provide information about the new technologies developed for the management of large data. Featuring coverage on a broad range of topics such as text and web data analytics, risk analysis, and opinion mining, this publication is ideally designed for professionals, researchers, and students seeking current research on various concepts of big data analytics.Topics Covered:The many academic areas covered in this publication include, but are not limited to:Data visualizationDistributed Computing SystemsOpinion MiningPrivacy and securityRisk analysisSocial Network AnalysisText Data AnalyticsWeb Data Analytics
Автор: Francesco Masulli; Alfredo Petrosino; Stefano Rove Название: Clustering High--Dimensional Data ISBN: 3662485761 ISBN-13(EAN): 9783662485767 Издательство: Springer Рейтинг: Цена: 37270.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the proceedings of the International Workshop on Clustering High-Dimensional Data, CHDD 2012, held in Naples, Italy, in May 2012. and the most common approach to tackle dimensionality problems, namely, dimensionality reduction and its application in clustering.
Автор: Olfa Nasraoui; Chiheb-Eddine Ben N`Cir Название: Clustering Methods for Big Data Analytics ISBN: 3030074196 ISBN-13(EAN): 9783030074197 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems. The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of data; clustering Big Data Streams such as streams generated by the confluence of Internet of Things, digital and mobile health, human-robot interaction, and social networks; Spark-based Big Data clustering using Particle Swarm Optimization; and Tensor-based clustering for Web graphs, sensor streams, and social networks. The chapters in the book include a balanced coverage of big data clustering theory, methods, tools, frameworks, applications, representation, visualization, and clustering validation.
Автор: Tin-Chih Toly Chen; Katsuhiro Honda Название: Fuzzy Collaborative Forecasting and Clustering ISBN: 3030225739 ISBN-13(EAN): 9783030225735 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book introduces the basic concepts of fuzzy collaborative forecasting and clustering, including its methodology, system architecture, and applications. It demonstrates how dealing with disparate data sources is becoming more and more popular due to the increasing spread of internet applications. The book proposes the concepts of collaborative computing intelligence and collaborative fuzzy modeling, and establishes several so-called fuzzy collaborative systems. It shows how technical constraints, security issues, and privacy considerations often limit access to some sources. This book is a valuable source of information for postgraduates, researchers and fuzzy control system developers, as it presents a very effective fuzzy approach that can deal with disparate data sources, big data, and multiple expert decision making.
Автор: Ujjwal Maulik; Sanghamitra Bandyopadhyay; Anirban Название: Multiobjective Genetic Algorithms for Clustering ISBN: 3642439632 ISBN-13(EAN): 9783642439636 Издательство: Springer Рейтинг: Цена: 51200.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book covers clustering using multiobjective genetic algorithms, with extensive real-life application in data mining and bioinformatics. The authors offer instructions for relevant techniques, and demonstrate real-world applications in several disciplines.
Автор: Junjie Wu Название: Advances in K-means Clustering ISBN: 3642447570 ISBN-13(EAN): 9783642447570 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The K-means algorithm is commonly used in data mining and business intelligence. This award-winning research pioneers its application to the intricacies of `big data`, detailing a theoretical framework for aggregating and validating clusters with K-means.
Автор: Dmitri A. Viattchenin Название: A Heuristic Approach to Possibilistic Clustering: Algorithms and Applications ISBN: 364244301X ISBN-13(EAN): 9783642443015 Издательство: Springer Рейтинг: Цена: 113180.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In a new approach to possibilistic clustering, the sought clustering structure of the set is based directly on the formal definition of fuzzy cluster and possibilistic memberships are determined directly from the values of the pairwise similarity of objects.
Автор: Viattchenin Dmitri A Название: Heuristic Approach to Possibilistic Clustering: Algorithms a ISBN: 3642355358 ISBN-13(EAN): 9783642355356 Издательство: Springer Рейтинг: Цена: 130610.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In a new approach to possibilistic clustering, the sought clustering structure of the set is based directly on the formal definition of fuzzy cluster and possibilistic memberships are determined directly from the values of the pairwise similarity of objects.
Автор: Long, Bo , Zhang, Zhongfei , Yu, Philip S. Название: Relational Data Clustering ISBN: 0367384051 ISBN-13(EAN): 9780367384050 Издательство: Taylor&Francis Рейтинг: Цена: 63280.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
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.
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