Mobile Data Mining And Applications

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Mobile Data Mining And Applications

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Author : Hao Jiang
language : en
Publisher: Springer
Release Date : 2019-05-10

Mobile Data Mining And Applications written by Hao Jiang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-10 with Technology & Engineering categories.

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

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Author : Jesus Mena
language : en
Publisher: CRC Press
Release Date : 2016-04-19

Data Mining Mobile Devices written by Jesus Mena and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Business & Economics categories.

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

Pocket Data Mining

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Author : Mohamed Medhat Gaber
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-10-19

Pocket Data Mining written by Mohamed Medhat Gaber and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-19 with Technology & Engineering categories.

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.

Research And Trends In Data Mining Technologies And Applications

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Author : Taniar, David
language : en
Publisher: IGI Global
Release Date : 2006-10-31

Research And Trends In Data Mining Technologies And Applications written by Taniar, David and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-10-31 with Computers categories.

Activities in data warehousing and mining are constantly emerging. Data mining methods, algorithms, online analytical processes, data mart and practical issues consistently evolve, providing a challenge for professionals in the field. Research and Trends in Data Mining Technologies and Applications focuses on the integration between the fields of data warehousing and data mining, with emphasis on the applicability to real-world problems. This book provides an international perspective, highlighting solutions to some of researchers' toughest challenges. Developments in the knowledge discovery process, data models, structures, and design serve as answers and solutions to these emerging challenges.

Mobile Data Mining

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Author : Yuan Yao
language : en
Publisher: Springer
Release Date : 2018-10-31

Mobile Data Mining written by Yuan Yao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-31 with Computers categories.

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.

Data Mining And Machine Learning Applications

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Author : Rohit Raja
language : en
Publisher: John Wiley & Sons
Release Date : 2022-01-26

Data Mining And Machine Learning Applications written by Rohit Raja and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-26 with Computers categories.

DATA MINING AND MACHINE LEARNING APPLICATIONS The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate results. The most common technologies used include classification and clustering methods. Accuracy and error rates are calculated for regression and classification and clustering to find actual results through algorithms like support vector machines and neural networks with forward and backward propagation. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce and so forth. The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies. A discussion of real-time problems. Audience Industry and academic researchers, scientists, and engineers in information technology, data science and machine and deep learning, as well as artificial intelligence more broadly.

Advanced Data Mining And Applications

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Author : Jianxin Li
language : en
Publisher: Springer Nature
Release Date : 2019-11-16

Advanced Data Mining And Applications written by Jianxin Li and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-16 with Computers categories.

This book constitutes the proceedings of the 15th International Conference on Advanced Data Mining and Applications, ADMA 2019, held in Dalian, China in November 2019. The 39 full papers presented together with 26 short papers and 2 demo papers were carefully reviewed and selected from 170 submissions. The papers were organized in topical sections named: Data Mining Foundations; Classification and Clustering Methods; Recommender Systems; Social Network and Social Media; Behavior Modeling and User Profiling; Text and Multimedia Mining; Spatial-Temporal Data; Medical and Healthcare Data/Decision Analytics; and Other Applications.

Intelligent Data Mining

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Author : Da Ruan
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-08-24

Intelligent Data Mining written by Da Ruan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-08-24 with Mathematics categories.

"Intelligent Data Mining – Techniques and Applications" is an organized edited collection of contributed chapters covering basic knowledge for intelligent systems and data mining, applications in economic and management, industrial engineering and other related industrial applications. The main objective of this book is to gather a number of peer-reviewed high quality contributions in the relevant topic areas. The focus is especially on those chapters that provide theoretical/analytical solutions to the problems of real interest in intelligent techniques possibly combined with other traditional tools, for data mining and the corresponding applications to engineers and managers of different industrial sectors. Academic and applied researchers and research students working on data mining can also directly benefit from this book.

Context Aware Machine Learning And Mobile Data Analytics

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Author : Iqbal Sarker
language : en
Publisher:
Release Date : 2021

Context Aware Machine Learning And Mobile Data Analytics written by Iqbal Sarker and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.

This book offers a clear understanding of the concept of context-aware machine learning including an automated rule-based framework within the broad area of data science and analytics, particularly, with the aim of data-driven intelligent decision making. Thus, we have bestowed a comprehensive study on this topic that explores multi-dimensional contexts in machine learning modeling, context discretization with time-series modeling, contextual rule discovery and predictive analytics, recent-pattern or rule-based behavior modeling, and their usefulness in various context-aware intelligent applications and services. The presented machine learning-based techniques can be employed in a wide range of real-world application areas ranging from personalized mobile services to security intelligence, highlighted in the book. As the interpretability of a rule-based system is high, the automation in discovering rules from contextual raw data can make this book more impactful for the application developers as well as researchers. Overall, this book provides a good reference for both academia and industry people in the broad area of data science, machine learning, AI-Driven computing, human-centered computing and personalization, behavioral analytics, IoT and mobile applications, and cybersecurity intelligence.

Data Mining In Dynamic Social Networks And Fuzzy Systems

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Author : Bhatnagar, Vishal
language : en
Publisher: IGI Global
Release Date : 2013-06-30

Data Mining In Dynamic Social Networks And Fuzzy Systems written by Bhatnagar, Vishal and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-30 with Computers categories.

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.