Data Mining Mobile Devices 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 Data Mining Mobile Devices PDF full book. Access full book title Data Mining Mobile Devices.
Author | : Jesus Mena |
Publisher | : CRC Press |
Total Pages | : 317 |
Release | : 2016-04-19 |
Genre | : Business & Economics |
ISBN | : 1466555963 |
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
Author | : Jesus Mena |
Publisher | : CRC Press |
Total Pages | : 325 |
Release | : 2016-04-19 |
Genre | : Business & Economics |
ISBN | : 1040059465 |
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
Author | : Muzammil Khan |
Publisher | : |
Total Pages | : 0 |
Release | : 2013-09-21 |
Genre | : |
ISBN | : 9783659463549 |
Download Interactive Data Mining Results Visualization on Mobile Devices Book in PDF, ePub and Kindle
Author | : Mohamed Medhat Gaber |
Publisher | : Springer Science & Business Media |
Total Pages | : 112 |
Release | : 2013-10-19 |
Genre | : Technology & Engineering |
ISBN | : 3319027115 |
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.
Author | : Cram101 Textbook Reviews |
Publisher | : Cram101 |
Total Pages | : 58 |
Release | : 2013-08 |
Genre | : |
ISBN | : 9781490246703 |
Download Studyguide for Data Mining Mobile Devices by Mena, Jesus, Isbn 9781466555952 Book in PDF, ePub and Kindle
Never HIGHLIGHT a Book Again! Includes all testable terms, concepts, persons, places, and events. Cram101 Just the FACTS101 studyguides gives all of the outlines, highlights, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanies: 9781466555952. This item is printed on demand.
Author | : Yuan Yao |
Publisher | : Springer |
Total Pages | : 58 |
Release | : 2018-10-31 |
Genre | : Computers |
ISBN | : 3030021017 |
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.
Author | : Hao Jiang |
Publisher | : Springer |
Total Pages | : 227 |
Release | : 2019-05-10 |
Genre | : Technology & Engineering |
ISBN | : 3030165035 |
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.
Author | : Aaron K. Baughman |
Publisher | : Springer |
Total Pages | : 452 |
Release | : 2015-03-31 |
Genre | : Computers |
ISBN | : 3319149989 |
Download Multimedia Data Mining and Analytics Book in PDF, ePub and Kindle
This book provides fresh insights into the cutting edge of multimedia data mining, reflecting how the research focus has shifted towards networked social communities, mobile devices and sensors. The work describes how the history of multimedia data processing can be viewed as a sequence of disruptive innovations. Across the chapters, the discussion covers the practical frameworks, libraries, and open source software that enable the development of ground-breaking research into practical applications. Features: reviews how innovations in mobile, social, cognitive, cloud and organic based computing impacts upon the development of multimedia data mining; provides practical details on implementing the technology for solving real-world problems; includes chapters devoted to privacy issues in multimedia social environments and large-scale biometric data processing; covers content and concept based multimedia search and advanced algorithms for multimedia data representation, processing and visualization.
Author | : Jesus Mena |
Publisher | : Butterworth-Heinemann |
Total Pages | : 476 |
Release | : 2003 |
Genre | : Business & Economics |
ISBN | : 9780750676137 |
Download Investigative Data Mining for Security and Criminal Detection Book in PDF, ePub and Kindle
Publisher Description
Author | : Charu C. Aggarwal |
Publisher | : Springer Science & Business Media |
Total Pages | : 547 |
Release | : 2013-01-15 |
Genre | : Computers |
ISBN | : 1461463092 |
Download Managing and Mining Sensor Data Book in PDF, ePub and Kindle
Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. In particular sensor notes have become cheaper and more efficient, and have even been integrated into day-to-day devices of use, such as mobile phones. This has lead to a much larger scale of applicability and mining of sensor data sets. The human-centric aspect of sensor data has created tremendous opportunities in integrating social aspects of sensor data collection into the mining process. Managing and Mining Sensor Data is a contributed volume by prominent leaders in this field, targeting advanced-level students in computer science as a secondary text book or reference. Practitioners and researchers working in this field will also find this book useful.