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Stream Data Mining: Algorithms and Their Probabilistic Properties

This book presents a unique approach to stream data mining. Unlike the vast majority of previous approaches, which are largely based on;

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Data Mining and Machine Learning

The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze;

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Data Streams

network traffic analysis, mining text message streams and processing massive data sets in general. Data Streams surveys the emerging area;

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Data Mining

in data mining literature and those not fully covered in most of existing literature due to their considerable difficulty. The book presents a;

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Data Mining

in data mining literature and those not fully covered in most of existing literature due to their considerable difficulty. The book presents a;

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Data Mining Concept Animation Library

algorithms, we need a better perspective on a collection of data mining algorithms rather than just their formal definitions. In this research work;

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Advances in Knowledge Discovery and Data Mining

; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms;

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Advances in Knowledge Discovery and Data Mining

; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms;

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Data Mining and Applications in Genomics

Data Mining and Applications in Genomics contains the data mining algorithms and their applications in genomics, with frontier case studies;

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Data Mining and Applications in Genomics

Data Mining and Applications in Genomics contains the data mining algorithms and their applications in genomics, with frontier case studies;

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Mining of Massive Datasets

the tricks of locality-sensitive hashing and stream-processing algorithms for mining data that arrives too fast for exhaustive processing;

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Data Stream Mining & Processing

This book constitutes the proceedings of the third International Conference on Data Stream and Mining and Processing, DSMP 2020, held;

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Mining of Massive Datasets

explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing;

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Data Mining Algorithms

evaluation, and creating model ensembles. The author presents many of the important topics and methodologies widely used in data mining, whilst;

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Data Mining and Knowledge Discovery With Evolutionary Algorithms

increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting;

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Probabilistic Data Structures and Algorithms for Big Data Applications

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Principles of Data Mining

algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how;

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Data Mining Tools for Malware Detection

Although the use of data mining for security and malware detection is quickly on the rise, most books on the subject provide high-level;

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Robust Data Mining

data mining techniques aim to create new algorithms resilient to error and noise. This work encapsulates all the latest applications of robust;

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Spatiotemporal Frequent Pattern Mining from Evolving Region Trajectories

perspective of relationship modeling among the spatiotemporal objects, frequent pattern mining algorithms, and data access methodologies for mining;

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Data Mining Algorithms

Researchers and Professionals in data mining and related fields should be familiar with different models and standard algorithms in use to;

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Artificial Intelligence and Soft Computing

parameter optimization with nature-inspired algorithms; special session: stream data mining.;

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Introduction to Data Mining

Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each major;

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Database Systems for Advanced Applications

management, database for emerging hardware, data mining, probabilistic and uncertain data management, web and social data management, security;

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Data Mining and Knowledge Discovery for Geoscientists

accessible to geoscientists, engineers, researchers and programmers in data miningIntroduces widely used algorithms, their basic principles;

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Managing Data Mining Technologies in Organizations

their applications for data mining. The chapters illustrate applications of data mining and visualization for credit screening, forecasting;

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Big Data

of resource-intensive computational settings Big Data Stream Techniques and Algorithms-explores research issues regarding the management and;

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