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Cognitive Social Mining Applications in Data Analytics and Forensics

of mining the social data. Cognitive Social Mining Applications in Data Analytics and Forensics is an essential reference source that reviews;

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Big Data Analytics and Computing for Digital Forensic Investigations

mining, big data analysis and decision mining. Dr Sachi Nandan Mohanty is an associate professor in the Department of Computer Science and;

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Trends and Applications in Knowledge Discovery and Data Mining

Knowledge Discovery and Data Mining (PAKDD) held in Tainan, Taiwan, in May 2014. The 73 revised papers presented were carefully reviewed and;

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Advanced Data Mining and Applications

; Recommender Systems; Social Network and Social Media; Behavior Modeling and User Profiling; Text and Multimedia Mining; Spatial-Temporal Data; Medical;

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Getting Started with Business Analytics

for integrating business with analytics. The second part presents the technologies underlying business analytics: data mining and data;

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Data Mining and Learning Analytics

Addresses the impacts of data mining on education and reviews applications in educational research teaching, and learning This book;

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Big-Data Analytics for Cloud, IoT and Cognitive Computing

The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main;

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Machine Learning and Big Data Analytics Paradigms

many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for;

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Data Mining for Business Analytics

Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts;

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Data Mining for Business Analytics

Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and;

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Text Analytics

Focusing on methodologies, applications and challenges of textual data analysis and related fields, this book gathers selected and peer;

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Data Mining For Business Analytics

Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro(R) presents an applied and interactive approach to;

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Data Analytics, Computational Statistics, and Operations Research for Engineers

, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications;

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Advanced Data Mining and Applications

This book constitutes the proceedings of the 16th International Conference on Advanced Data Mining and Applications, ADMA 2020, held;

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Future Data and Security Engineering

selected from 88 submissions. They have been organized in the following topical sections: big data analytics and massive dataset mining; security;

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Rapidminer

and Business Analytics Applications provides an in-depth introduction to the application of data mining and business analytics techniques and;

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Mining Text Data

Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances;

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Mining Text Data

Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances;

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Data Analytics Applications in Gaming and Entertainment

game experiences to a wide range of preferences and skill levels. This, in turn, has led to a growing interest in data mining techniques, as;

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Data Analytics Applications in Gaming and Entertainment

game experiences to a wide range of preferences and skill levels. This, in turn, has led to a growing interest in data mining techniques, as;

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Machine Learning in Cognitive IoT

of machine learning (ML) in data mining. Further, it explains various ML techniques and paradigms with different phases of data pre-processing and;

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Mining Over Air

machine learning and data mining methodologies in the wireless networks domain. Mining Over Air describes the problems and their solutions for;

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Decision Trees for Business Intelligence and Data Mining

This example-driven guide illustrates the application and operation of decision trees in data mining, business intelligence, business;

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Advances in Knowledge Discovery and Data Mining

learning and embedding; mining behavioral data; deep learning; feature extraction and selection; human, domain, organizational and social factors;

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Advances in Knowledge Discovery and Data Mining

learning and embedding; mining behavioral data; deep learning; feature extraction and selection; human, domain, organizational and social factors;

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Web Technologies and Applications

, China, in September 2016: the Second International Workshop on Web Data Mining and Applications, WDMA 2016, the First International Workshop on;

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Big Data Analytics

sections named: big data analytics: vision and perspectives; financial data analytics and data streams; web and social media data; big data systems;

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