Mobile Data Mining and Applications

This book focuses on mobile data and its applications in the wireless networks of the future.

Mobile Data Mining and Applications

Author: Hao Jiang

Publisher: Springer

ISBN: 3030165035

Page: 227

View: 290

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.

Mobile Data Mining

The key idea behind these applications is to learn the facts of activities, events,
and situations where the users are involved together with smartphones. Existing
literature has also extensively studied the mobile data mining topic, which can be
 ...

Mobile Data Mining

Author: Yuan Yao

Publisher: Springer

ISBN: 3030021017

Page: 58

View: 808

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.

Advanced Data Mining and Applications

Since their arrival in 2007, smartphones have progressed from mobile phones
with basic apps to personal computers with ... Early attempts to incorporate local
data mining onto mobile devices included the 'Mobileminer' application [3] that ...

Advanced Data Mining and Applications

Author: Jianxin Li

Publisher: Springer Nature

ISBN: 3030352315

Page: 893

View: 940

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.

Real World Data Mining Applications

The aim of the proposed volume is to provide a balanced treatment of the latest advances and developments in data mining; in particular, exploring synergies at the intersection with information systems.

Real World Data Mining Applications

Author: Mahmoud Abou-Nasr

Publisher: Springer

ISBN: 3319078127

Page: 418

View: 392

Data mining applications range from commercial to social domains, with novel applications appearing swiftly; for example, within the context of social networks. The expanding application sphere and social reach of advanced data mining raise pertinent issues of privacy and security. Present-day data mining is a progressive multidisciplinary endeavor. This inter- and multidisciplinary approach is well reflected within the field of information systems. The information systems research addresses software and hardware requirements for supporting computationally and data-intensive applications. Furthermore, it encompasses analyzing system and data aspects, and all manual or automated activities. In that respect, research at the interface of information systems and data mining has significant potential to produce actionable knowledge vital for corporate decision-making. The aim of the proposed volume is to provide a balanced treatment of the latest advances and developments in data mining; in particular, exploring synergies at the intersection with information systems. It will serve as a platform for academics and practitioners to highlight their recent achievements and reveal potential opportunities in the field. Thanks to its multidisciplinary nature, the volume is expected to become a vital resource for a broad readership ranging from students, throughout engineers and developers, to researchers and academics.

Advanced Data Mining and Applications

Community Based User Behavior Analysis on Daily Mobile Internet Usage⋆
Jamal Yousaf, Juanzi Li, and Yuanchao Ma Department of Computer Science
and Technology, Tsinghua National Laboratory for Information Science and ...

Advanced Data Mining and Applications

Author: Hiroshi Motoda

Publisher: Springer

ISBN: 3642539149

Page: 588

View: 707

The two-volume set LNAI 8346 and 8347 constitutes the thoroughly refereed proceedings of the 9th International Conference on Advanced Data Mining and Applications, ADMA 2013, held in Hangzhou, China, in December 2013. The 32 regular papers and 64 short papers presented in these two volumes were carefully reviewed and selected from 222 submissions. The papers included in these two volumes cover the following topics: opinion mining, behavior mining, data stream mining, sequential data mining, web mining, image mining, text mining, social network mining, classification, clustering, association rule mining, pattern mining, regression, predication, feature extraction, identification, privacy preservation, applications, and machine learning.

Parallel and Distributed Processing and Applications

Mobile Data Mining involves the generation of interesting patterns out from
datasets collected from mobile devices. Previous work are frequency pattern [3],
group pattern [9] and parallel pattern [5]. As mobile applications usage increases,
the ...

Parallel and Distributed Processing and Applications

Author: Jiannong Cao

Publisher: Springer Science & Business Media

ISBN: 9783540241287

Page: 1058

View: 971

This book constitutes the refereed proceedings of the Second International Symposium on Parallel and Distributed Processing and Applications, ISPA 2004, held in Hong Kong, China in December 2004. The 78 revised full papers and 38 revised short papers presented were carefully reviewed and selected from 361 submissions. The papers are organized in topical sections on parallel algorithms and systems, data mining and management, distributed algorithms and systems, fault tolerance protocols and systems, sensor networks and protocols, cluster systems, grid applications and systems, peer-to-peer and ad hoc networking, grid scheduling and algorithms, data replication and caching, software engineering and testing, grid protocols, context-aware and mobile computing, distributed routing and switching protocols, cluster resource scheduling and algorithms, security, high performance processing, networking and protocols, artificial intelligence systems, hardware architecture and implementations, high performance computing architecture, and distributed systems architecture.

Advanced Data Mining and Applications

This book constitutes the refereed proceedings of the 13th International Conference on Advanced Data Mining and Applications, ADMA 2017, held in Singapore in November 2017.

Advanced Data Mining and Applications

Author: Gao Cong

Publisher: Springer

ISBN: 3319691791

Page: 881

View: 629

This book constitutes the refereed proceedings of the 13th International Conference on Advanced Data Mining and Applications, ADMA 2017, held in Singapore in November 2017. The 20 full and 38 short papers presented in this volume were carefully reviewed and selected from 118 submissions. The papers were organized in topical sections named: database and distributed machine learning; recommender system; social network and social media; machine learning; classification and clustering methods; behavior modeling and user profiling; bioinformatics and medical data analysis; spatio-temporal data; natural language processing and text mining; data mining applications; applications; and demos.

Data Mining for Geoinformatics

This book is designed for researchers and advanced-level students focused on computer science, earth science and geography as a reference or secondary text book.

Data Mining for Geoinformatics

Author: Guido Cervone

Publisher: Springer Science & Business Media

ISBN: 1461476690

Page: 166

View: 460

The rate at which geospatial data is being generated exceeds our computational capabilities to extract patterns for the understanding of a dynamically changing world. Geoinformatics and data mining focuses on the development and implementation of computational algorithms to solve these problems. This unique volume contains a collection of chapters on state-of-the-art data mining techniques applied to geoinformatic problems of high complexity and important societal value. Data Mining for Geoinformatics addresses current concerns and developments relating to spatio-temporal data mining issues in remotely-sensed data, problems in meteorological data such as tornado formation, estimation of radiation from the Fukushima nuclear power plant, simulations of traffic data using OpenStreetMap, real time traffic applications of data stream mining, visual analytics of traffic and weather data and the exploratory visualization of collective, mobile objects such as the flocking behavior of wild chickens. This book is designed for researchers and advanced-level students focused on computer science, earth science and geography as a reference or secondary text book. Practitioners working in the areas of data mining and geoscience will also find this book to be a valuable reference.

Practical Applications of Data Mining

Introduction to data mining -- Association rules -- Classification learning -- Statistics for data mining -- Rough sets and bayes theories -- Neural networks -- Clustering -- Fuzzy information retrieval.

Practical Applications of Data Mining

Author: Sang C. Suh

Publisher: Jones & Bartlett Publishers

ISBN: 0763785873

Page: 414

View: 417

Various topics of data mining techniques are identified and described throughout, including clustering, association rules, rough set theory, probability theory, neural networks, classification, and fuzzy logic. Each of these techniques is explored with a theoretical introduction and its effectiveness is demonstrated with various chapter examples.

Next Generation of Data Mining

After the description of two frameworks for designing data-mining applications on
wired grids, in this section, we present a mobile data-mining system based on a
wireless SOA. Here, we refer to mobile data mining as the process of using ...

Next Generation of Data Mining

Author: Hillol Kargupta

Publisher: CRC Press

ISBN: 9781420085877

Page: 601

View: 558

Drawn from the US National Science Foundation’s Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation (NGDM 07), Next Generation of Data Mining explores emerging technologies and applications in data mining as well as potential challenges faced by the field. Gathering perspectives from top experts across different disciplines, the book debates upcoming challenges and outlines computational methods. The contributors look at how ecology, astronomy, social science, medicine, finance, and more can benefit from the next generation of data mining techniques. They examine the algorithms, middleware, infrastructure, and privacy policies associated with ubiquitous, distributed, and high performance data mining. They also discuss the impact of new technologies, such as the semantic web, on data mining and provide recommendations for privacy-preserving mechanisms. The dramatic increase in the availability of massive, complex data from various sources is creating computing, storage, communication, and human-computer interaction challenges for data mining. Providing a framework to better understand these fundamental issues, this volume surveys promising approaches to data mining problems that span an array of disciplines.

Knowledge Discovery Practices and Emerging Applications of Data Mining

This book covers association mining, classification, mobile marketing, opinion mining, microarray data mining, internet mining and applications of data mining on biological data, telecommunication and distributed databases, among others, ...

Knowledge Discovery Practices and Emerging Applications of Data Mining

Author: A. Senthil kumar

Publisher: IGI Global

ISBN: 9781609600679

Page: 390

View: 297

Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains introduces the reader to recent research activities in the field of data mining. This book covers association mining, classification, mobile marketing, opinion mining, microarray data mining, internet mining and applications of data mining on biological data, telecommunication and distributed databases, among others, while promoting understanding and implementation of data mining techniques in emerging domains.

Advanced Data Mining and Applications

The two-volume set LNAI 7120 and LNAI 7121 constitutes the refereed proceedings of the 7th International Conference on Advanced Data Mining and Applications, ADMA 2011, held in Beijing, China, in December 2011.

Advanced Data Mining and Applications

Author: Jie Tang

Publisher: Springer Science & Business Media

ISBN: 3642258557

Page: 419

View: 898

The two-volume set LNAI 7120 and LNAI 7121 constitutes the refereed proceedings of the 7th International Conference on Advanced Data Mining and Applications, ADMA 2011, held in Beijing, China, in December 2011. The 35 revised full papers and 29 short papers presented together with 3 keynote speeches were carefully reviewed and selected from 191 submissions. The papers cover a wide range of topics presenting original research findings in data mining, spanning applications, algorithms, software and systems, and applied disciplines.

Trends and Applications in Knowledge Discovery and Data Mining

PAKDD has established itself as the premier event for data mining researchers in
the Pacific-Asia region. ... Public Health and Wellness (DMDA-Health),
Biologically Inspired Data Mining Techniques (BDM), Mobile Data Management,
Mining, ...

Trends and Applications in Knowledge Discovery and Data Mining

Author: Wen-Chih Peng

Publisher: Springer

ISBN: 3319131869

Page: 833

View: 613

This book constitutes the refereed proceedings at PAKDD Workshops 2014, held in conjunction with the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) held in Tainan, Taiwan, in May 2014. The 73 revised papers presented were carefully reviewed and selected from 179 submissions. The workshops affiliated with PAKDD 2014 include: Data Analytics for Targeted Healthcare, DANTH; Data Mining and Decision Analytics for Public Health and Wellness, DMDA-Health; Biologically Inspired Data Mining Techniques, BDM; Mobile Data Management, Mining, and Computing on Social Networks, MobiSocial; Big Data Science and Engineering on E-Commerce, BigEC; Cloud Service Discovery, CloudSD; Mobile Sensing, Mining and Visualization for Human Behavior Inferences, MSMV-HBI; Scalable Dats Analytics: Theory and Algorithms, SDA; Algorithms for Large-Scale Information Processing in Knowledge Discovery, ALSIP; Data Mining in Social Networks, SocNet; Data Mining in Biomedical Informatics and Healthcare, DMBIH; and Pattern Mining and Application of Big Data, BigPMA.

Advances in Data Mining Applications and Theoretical Aspects

This book constitutes the refereed proceedings of the 16th Industrial Conference on Advances in Data Mining, ICDM 2016, held in New York, NY, USA, in July 2016.

Advances in Data Mining  Applications and Theoretical Aspects

Author: Petra Perner

Publisher: Springer

ISBN: 3319415611

Page: 446

View: 392

This book constitutes the refereed proceedings of the 16th Industrial Conference on Advances in Data Mining, ICDM 2016, held in New York, NY, USA, in July 2016. The 33 revised full papers presented were carefully reviewed and selected from 100 submissions. The topics range from theoretical aspects of data mining to applications of data mining, such as in multimedia data, in marketing, in medicine, and in process control, industry, and society.

Data Warehousing and Mining Concepts Methodologies Tools and Applications

Concepts, Methodologies, Tools, and Applications Wang, John ... As a result, the
usage of data mining to analyse clickstream data collected from users of mobile
devices to predict the user's interest is not going to be accurate. Security and ...

Data Warehousing and Mining  Concepts  Methodologies  Tools  and Applications

Author: Wang, John

Publisher: IGI Global

ISBN: 159904952X

Page: 4092

View: 531

In recent years, the science of managing and analyzing large datasets has emerged as a critical area of research. In the race to answer vital questions and make knowledgeable decisions, impressive amounts of data are now being generated at a rapid pace, increasing the opportunities and challenges associated with the ability to effectively analyze this data.

Pocket Data Mining

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.

Pocket Data Mining

Author: Mohamed Medhat Gaber

Publisher: Springer Science & Business Media

ISBN: 3319027115

Page: 108

View: 154

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 Techniques and Applications

Covering not only traditional areas of data mining such as association, clustering and classification, this text also explains topics such as data warehousing, online-analytic processing, and text mining.

Data Mining Techniques and Applications

Author: Hongbo Du

Publisher:

ISBN: 9781844808915

Page: 315

View: 148

This concise and approachable introduction to data mining selects a mixture of data mining techniques originating from statistics, machine learning and databases, and presents them in an algorithmic approach. Aimed primarily at undergraduate readers, it presents not only the fundamental principles and concepts of the subject in an easy-to-understand way, but also hands on, practical instruction on data mining techniques, that readers can put into practice as they go along using the freely downloadable Weka toolkit. Author Hongbo Du shares his years of commercial, as well as research-based, experience in the field through extensive examples and real-world case studies, highlighting how data mining solutions provided by software tools are used in practical problem solving. Covering not only traditional areas of data mining such as association, clustering and classification, this text also explains topics such as data warehousing, online-analytic processing, and text mining.

Data Mining Concepts Methodologies Tools and Applications

Data Mining: Concepts, Methodologies, Tools, and Applications is a comprehensive collection of research on the latest advancements and developments of data mining and how it fits into the current technological world.

Data Mining  Concepts  Methodologies  Tools  and Applications

Author: Management Association, Information Resources

Publisher: IGI Global

ISBN: 1466624566

Page: 2120

View: 622

Data mining continues to be an emerging interdisciplinary field that offers the ability to extract information from an existing data set and translate that knowledge for end-users into an understandable way. Data Mining: Concepts, Methodologies, Tools, and Applications is a comprehensive collection of research on the latest advancements and developments of data mining and how it fits into the current technological world.

Emerging Technologies in Knowledge Discovery and Data Mining

Mining information from distributed data sources over the Internet is a growing
research area. The introduction of mobile agent paradigm opens a new door for
distributed data mining and knowledge discovery applications. In this paper, we ...

Emerging Technologies in Knowledge Discovery and Data Mining

Author: Takashi Washio

Publisher: Springer Science & Business Media

ISBN: 354077016X

Page: 678

View: 216

This book constitutes the thoroughly refereed post-proceedings of three workshops and an industrial track held in conjunction with the 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007, held in Nanjing, China in May 2007. The 62 revised full papers presented together with an overview article to each workshop were carefully reviewed and selected from 355 submissions.