Mobile Data Mining PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Mobile Data Mining PDF full book. Access full book title Mobile Data Mining.

Mobile Data Mining and Applications

Mobile Data Mining and Applications
Author: Hao Jiang
Publisher: Springer
Total Pages: 227
Release: 2019-05-10
Genre: Technology & Engineering
ISBN: 3030165035
GET BOOK

Download Mobile Data Mining and Applications Book in PDF, ePub and Kindle

This book focuses on mobile data and its applications in the wireless networks of the future. Several topics form the basis of discussion, from a mobile data mining platform for collecting mobile data, to mobile data processing, and mobile feature discovery. Usage of mobile data mining is addressed in the context of three applications: wireless communication optimization, applications of mobile data mining on the cellular networks of the future, and how mobile data shapes future cities. In the discussion of wireless communication optimization, both licensed and unlicensed spectra are exploited. Advanced topics include mobile offloading, resource sharing, user association, network selection and network coexistence. Mathematical tools, such as traditional convexappl/non-convex, stochastic processing and game theory are used to find objective solutions. Discussion of the applications of mobile data mining to cellular networks of the future includes topics such as green communication networks, 5G networks, and studies of the problems of cell zooming, power control, sleep/wake, and energy saving. The discussion of mobile data mining in the context of smart cities of the future covers applications in urban planning and environmental monitoring: the technologies of deep learning, neural networks, complex networks, and network embedded data mining. Mobile Data Mining and Applications will be of interest to wireless operators, companies, governments as well as interested end users.

Data Mining Mobile Devices

Data Mining Mobile Devices
Author: Jesus Mena
Publisher: CRC Press
Total Pages: 325
Release: 2013-06-18
Genre: Business & Economics
ISBN: 1466555955
GET BOOK

Download Data Mining Mobile Devices Book in PDF, ePub and Kindle

With today’s consumers spending more time on their mobiles than on their PCs, new methods of empirical stochastic modeling have emerged that can provide marketers with detailed information about the products, content, and services their customers desire. Data Mining Mobile Devices defines the collection of machine-sensed environmental data pertaining to human social behavior. It explains how the integration of data mining and machine learning can enable the modeling of conversation context, proximity sensing, and geospatial location throughout large communities of mobile users. Examines the construction and leveraging of mobile sites Describes how to use mobile apps to gather key data about consumers’ behavior and preferences Discusses mobile mobs, which can be differentiated as distinct marketplaces—including Apple®, Google®, Facebook®, Amazon®, and Twitter® Provides detailed coverage of mobile analytics via clustering, text, and classification AI software and techniques Mobile devices serve as detailed diaries of a person, continuously and intimately broadcasting where, how, when, and what products, services, and content your consumers desire. The future is mobile—data mining starts and stops in consumers' pockets. Describing how to analyze Wi-Fi and GPS data from websites and apps, the book explains how to model mined data through the use of artificial intelligence software. It also discusses the monetization of mobile devices’ desires and preferences that can lead to the triangulated marketing of content, products, or services to billions of consumers—in a relevant, anonymous, and personal manner.

Mobile Data Mining

Mobile Data Mining
Author: Yuan Yao
Publisher: Springer
Total Pages: 58
Release: 2018-10-31
Genre: Computers
ISBN: 3030021017
GET BOOK

Download Mobile Data Mining Book in PDF, ePub and Kindle

This SpringerBrief presents a typical life-cycle of mobile data mining applications, including: data capturing and processing which determines what data to collect, how to collect these data, and how to reduce the noise in the data based on smartphone sensors feature engineering which extracts and selects features to serve as the input of algorithms based on the collected and processed data model and algorithm design In particular, this brief concentrates on the model and algorithm design aspect, and explains three challenging requirements of mobile data mining applications: energy-saving, personalization, and real-time Energy saving is a fundamental requirement of mobile applications, due to the limited battery capacity of smartphones. The authors explore the existing practices in the methodology level (e.g. by designing hierarchical models) for saving energy. Another fundamental requirement of mobile applications is personalization. Most of the existing methods tend to train generic models for all users, but the authors provide existing personalized treatments for mobile applications, as the behaviors may differ greatly from one user to another in many mobile applications. The third requirement is real-time. That is, the mobile application should return responses in a real-time manner, meanwhile balancing effectiveness and efficiency. This SpringerBrief targets data mining and machine learning researchers and practitioners working in these related fields. Advanced level students studying computer science and electrical engineering will also find this brief useful as a study guide.

Pocket Data Mining

Pocket Data Mining
Author: Mohamed Medhat Gaber
Publisher: Springer Science & Business Media
Total Pages: 112
Release: 2013-10-19
Genre: Technology & Engineering
ISBN: 3319027115
GET BOOK

Download Pocket Data Mining Book in PDF, ePub and Kindle

Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the deployment of PDM in the mobile environment. An important extension to the basic implementation of PDM dealing with concept drift is also reported. In the era of Big Data, potential applications of paramount importance offered by PDM in a variety of domains including security, business and telemedicine are discussed.

Data Mining

Data Mining
Author: Ian H. Witten
Publisher: Elsevier
Total Pages: 665
Release: 2011-02-03
Genre: Computers
ISBN: 0080890369
GET BOOK

Download Data Mining Book in PDF, ePub and Kindle

Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks—in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization

Data Mining Mobile Devices

Data Mining Mobile Devices
Author: Jesus Mena
Publisher: CRC Press
Total Pages: 317
Release: 2016-04-19
Genre: Business & Economics
ISBN: 1466555963
GET BOOK

Download Data Mining Mobile Devices Book in PDF, ePub and Kindle

With today's consumers spending more time on their mobiles than on their PCs, new methods of empirical stochastic modeling have emerged that can provide marketers with detailed information about the products, content, and services their customers desire.Data Mining Mobile Devices defines the collection of machine-sensed environmental data pertainin

Data Mining: Concepts and Techniques

Data Mining: Concepts and Techniques
Author: Jiawei Han
Publisher: Elsevier
Total Pages: 740
Release: 2011-06-09
Genre: Computers
ISBN: 0123814804
GET BOOK

Download Data Mining: Concepts and Techniques Book in PDF, ePub and Kindle

Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data

Advanced Data Mining Techniques

Advanced Data Mining Techniques
Author: David L. Olson
Publisher: Springer Science & Business Media
Total Pages: 182
Release: 2008-01-01
Genre: Business & Economics
ISBN: 354076917X
GET BOOK

Download Advanced Data Mining Techniques Book in PDF, ePub and Kindle

This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focuses on business applications of data mining.

Mobility, Data Mining and Privacy

Mobility, Data Mining and Privacy
Author: Fosca Giannotti
Publisher: Springer Science & Business Media
Total Pages: 415
Release: 2008-01-12
Genre: Computers
ISBN: 3540751777
GET BOOK

Download Mobility, Data Mining and Privacy Book in PDF, ePub and Kindle

Mobile communications and ubiquitous computing generate large volumes of data. Mining this data can produce useful knowledge, yet individual privacy is at risk. This book investigates the various scientific and technological issues of mobility data, open problems, and roadmap. The editors manage a research project called GeoPKDD, Geographic Privacy-Aware Knowledge Discovery and Delivery, and this book relates their findings in 13 chapters covering all related subjects.

Data Mining in Dynamic Social Networks and Fuzzy Systems

Data Mining in Dynamic Social Networks and Fuzzy Systems
Author: Bhatnagar, Vishal
Publisher: IGI Global
Total Pages: 412
Release: 2013-06-30
Genre: Computers
ISBN: 1466642149
GET BOOK

Download Data Mining in Dynamic Social Networks and Fuzzy Systems Book in PDF, ePub and Kindle

Many organizations, whether in the public or private sector, have begun to take advantage of the tools and techniques used for data mining. Utilizing data mining tools, these organizations are able to reveal the hidden and unknown information from available data. Data Mining in Dynamic Social Networks and Fuzzy Systems brings together research on the latest trends and patterns of data mining tools and techniques in dynamic social networks and fuzzy systems. With these improved modern techniques of data mining, this publication aims to provide insight and support to researchers and professionals concerned with the management of expertise, knowledge, information, and organizational development.