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Mobile Data Mining, Yuan Yao; Xing Su; Hanghang Tong


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Автор: Yuan Yao; Xing Su; Hanghang Tong
Название:  Mobile Data Mining
ISBN: 9783030021009
Издательство: Springer
Классификация:



ISBN-10: 3030021009
Обложка/Формат: Soft cover
Страницы: 58
Вес: 0.16 кг.
Дата издания: 2018
Серия: SpringerBriefs in Computer Science
Язык: English
Издание: 1st ed. 2018
Иллюстрации: 25 tables, color; 22 illustrations, color; ix, 58 p. 22 illus. in color.
Размер: 235 x 155
Читательская аудитория: Professional & vocational
Основная тема: Computer Science
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: 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 designIn 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.
Дополнительное описание: 1 Introduction.- 2 Data Capturing and Processing.- 3 Feature Engineering.- 4 Hierarchical Model.- 5 Personalized Model.- 6 Online Model.- 7 Conclusions.


Mining of Massive Datasets

Автор: Leskovec Jure
Название: Mining of Massive Datasets
ISBN: 1108476341 ISBN-13(EAN): 9781108476348
Издательство: Cambridge Academ
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Цена: 71810.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Essential reading for students and practitioners, this book focuses on practical algorithms used to solve key problems in data mining, with exercises suitable for students from the advanced undergraduate level and beyond. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.

Oracle pl/sql interview questions you`ll most likely be asked

Автор: Vibrant Publishers
Название: Oracle pl/sql interview questions you`ll most likely be asked
ISBN: 1946383112 ISBN-13(EAN): 9781946383112
Издательство: Gazelle Book Services
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Цена: 26020.00 T
Наличие на складе: Есть
Описание:

  • 261 ORACLE PL/SQL Interview Questions
  • Dozens of examples
  • 77 HR Questions with Answers
  • 2 Aptitude Tests

ORACLE PL/SQL Interview Questions You'll Most Likely Be Asked is arguably the future for enterprise information systems. Corporations, both large and small, are looking for resources who know their job in depth. ORACLE PL/SQL Interview Questions You'll Most Likely Be Asked is a perfect companion to stand a head above the rest in today's competitive job market. Rather than going through comprehensive, textbook-sized reference guides, this book includes only the information required immediately for job search to build a career as a ORACLE PL/SQL Professional. If you think this book just covers important topics in brief, then you are mistaken It covers questions those are based on project knowledge and experience gained on successful high-profile ORACLE implementers. This book puts the interviewee in the driver's seat and helps them steer their way to impress the interviewer.

Includes:

(a) 261 ORACLE PL/SQL Interview Questions, Answers and Proven Strategies for getting hired as an ORACLE PL/SQL Professional

(b) Dozens of examples to respond to interview questions

(c) 77 HR Questions with Answers and Proven strategies to give specific, impressive, answers that help nail the interviews

(d) 2 Aptitude Tests included on the CD-ROM


Data Science For Business: What You Need To Know About Data Mining And Dataanalytic Thinking

Автор: Foster Provost
Название: Data Science For Business: What You Need To Know About Data Mining And Dataanalytic Thinking
ISBN: 1449361323 ISBN-13(EAN): 9781449361327
Издательство: Wiley
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Цена: 42230.00 T
Наличие на складе: Есть
Описание: This broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect.

Handbook of Statistical Analysis and Data Mining Applications, 2 ed.

Автор: Robert Nisbet , Gary Miner, Ken Yale
Название: Handbook of Statistical Analysis and Data Mining Applications, 2 ed.
ISBN: 0124166326 ISBN-13(EAN): 9780124166325
Издательство: Elsevier Science
Рейтинг:
Цена: 88690.00 T
Наличие на складе: Нет в наличии.
Описание:

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application.

This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas--from science and engineering, to medicine, academia and commerce.

  • Includes input by practitioners for practitioners
  • Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models
  • Contains practical advice from successful real-world implementations
  • Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions
  • Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner

Автор: Galit Shmueli, Peter C. Bruce, Nitin R. Patel
Название: Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner
ISBN: 1118729277 ISBN-13(EAN): 9781118729274
Издательство: Wiley
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Цена: 118270.00 T
Наличие на складе: Нет в наличии.
Описание: Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies.

Music Data Mining

Автор: Tao Li; Mitsunori Ogihara; George Tzanetakis
Название: Music Data Mining
ISBN: 1439835527 ISBN-13(EAN): 9781439835524
Издательство: Taylor&Francis
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Цена: 112290.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

The research area of music information retrieval has gradually evolved to address the challenges of effectively accessing and interacting large collections of music and associated data, such as styles, artists, lyrics, and reviews. Bringing together an interdisciplinary array of top researchers, Music Data Mining presents a variety of approaches to successfully employ data mining techniques for the purpose of music processing.

The book first covers music data mining tasks and algorithms and audio feature extraction, providing a framework for subsequent chapters. With a focus on data classification, it then describes a computational approach inspired by human auditory perception and examines instrument recognition, the effects of music on moods and emotions, and the connections between power laws and music aesthetics. Given the importance of social aspects in understanding music, the text addresses the use of the Web and peer-to-peer networks for both music data mining and evaluating music mining tasks and algorithms. It also discusses indexing with tags and explains how data can be collected using online human computation games. The final chapters offer a balanced exploration of hit song science as well as a look at symbolic musicology and data mining.

The multifaceted nature of music information often requires algorithms and systems using sophisticated signal processing and machine learning techniques to better extract useful information. An excellent introduction to the field, this volume presents state-of-the-art techniques in music data mining and information retrieval to create novel ways of interacting with large music collections.


Materials Informatics: Methods, Tools, and Applications

Автор: Isayev O
Название: Materials Informatics: Methods, Tools, and Applications
ISBN: 3527341218 ISBN-13(EAN): 9783527341214
Издательство: Wiley
Рейтинг:
Цена: 102380.00 T
Наличие на складе: Нет в наличии.
Описание: Provides everything readers need to know for applying the power of informatics to materials science

There is a tremendous interest in materials informatics and application of data mining to materials science. This book is a one-stop guide to the latest advances in these emerging fields. Bridging the gap between materials science and informatics, it introduces readers to up-to-date data mining and machine learning methods. It also provides an overview of state-of-the-art software and tools. Case studies illustrate the power of materials informatics in guiding the experimental discovery of new materials.

Materials Informatics: Methods, Tools and Applications is presented in two parts?Methodological Aspects of Materials Informatics and Practical Aspects and Applications. The first part focuses on developments in software, databases, and high-throughput computational activities. Chapter topics include open quantum materials databases; the ICSD database; open crystallography databases; and more. The second addresses the latest developments in data mining and machine learning for materials science. Its chapters cover genetic algorithms and crystal structure prediction; MQSPR modeling in materials informatics; prediction of materials properties; amongst others.

-Bridges the gap between materials science and informatics
-Covers all the known methodologies and applications of materials informatics
-Presents case studies that illustrate the power of materials informatics in guiding the experimental quest for new materials
-Examines the state-of-the-art software and tools being used today

Materials Informatics: Methods, Tools and Applications is a must-have resource for materials scientists, chemists, and engineers interested in the methods of materials informatics.

Sport Business Analytics

Автор: C. Keith Harrison, Scott Bukstein
Название: Sport Business Analytics
ISBN: 1498761267 ISBN-13(EAN): 9781498761260
Издательство: Taylor&Francis
Рейтинг:
Цена: 117390.00 T
Наличие на складе: Нет в наличии.
Описание:

Developing and implementing a systematic analytics strategy can result in a sustainable competitive advantage within the sport business industry. This timely and relevant book provides practical strategies to collect data and then convert that data into meaningful, value-added information and actionable insights. Its primary objective is to help sport business organizations utilize data-driven decision-making to generate optimal revenue from such areas as ticket sales and corporate partnerships. To that end, the book includes in-depth case studies from such leading sports organizations as the Orlando Magic, Tampa Bay Buccaneers, Duke University, and the Aspire Group.

The core purpose of sport business analytics is to convert raw data into information that enables sport business professionals to make strategic business decisions that result in improved company financial performance and a measurable and sustainable competitive advantage. Readers will learn about the role of big data and analytics in:

  • Ticket pricing
  • Season ticket member retention
  • Fan engagement
  • Sponsorship valuation
  • Customer relationship management
  • Digital marketing
  • Market research
  • Data visualization.

This book examines changes in the ticketing marketplace and spotlights innovative ticketing strategies used in various sport organizations. It shows how to engage fans with social media and digital analytics, presents techniques to analyze engagement and marketing strategies, and explains how to utilize analytics to leverage fan engagement to enhance revenue for sport organizations.

Filled with insightful case studies, this book benefits both sports business professionals and students. The concluding chapter on teaching sport analytics further enhances its value to academics.

Mobile Data Mining and Applications

Автор: Hao Jiang; Qimei Chen; Yuanyuan Zeng; Deshi Li
Название: Mobile Data Mining and Applications
ISBN: 3030165027 ISBN-13(EAN): 9783030165024
Издательство: Springer
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Цена: 121110.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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

Автор: Mena, Jesus
Название: Data Mining Mobile Devices
ISBN: 0367379899 ISBN-13(EAN): 9780367379896
Издательство: Taylor&Francis
Рейтинг:
Цена: 60220.00 T
Наличие на складе: Нет в наличии.
Описание:

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(R), Google(R), Facebook(R), Amazon(R), and Twitter(R)
  • 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 and Applications

Автор: Jiang Hao, Chen Qimei, Zeng Yuanyuan
Название: Mobile Data Mining and Applications
ISBN: 3030165051 ISBN-13(EAN): 9783030165055
Издательство: Springer
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Цена: 121110.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.

Handbook of Research on Advances in Data Analytics and Complex Communication Networks

Автор: Krishna P. Venkata
Название: Handbook of Research on Advances in Data Analytics and Complex Communication Networks
ISBN: 1799876853 ISBN-13(EAN): 9781799876854
Издательство: Mare Nostrum (Eurospan)
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Цена: 366830.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The use of the internet has increased with the introduction of wireless systems and the internet of things (IoT). The growth of smart devices helps to create a new generation and knowledge-sharing platforms. Namely, data analytics has a major role to play in this growth and the success of wireless and IoT applications. The growth of data has become exponential, and it is difficult to analyze with respect to complex communication networks, hence the need for research in the field to understand both big data and these communication networks. Additionally, there are many unforeseen challenges that can emerge and disrupt the normal flow of things, such as the global COVID-19 pandemic, which produce more stress on current systems and technologies. The study of IoT, data analytics, and complex communication networks is essential in current times.

The Handbook of Research on Advances in Data Analytics and Complex Communication Networks discusses and addresses the issues and challenges of the development of various systems using data analytics and complex communication networks. The chapters identify different issues, suggest feasible solutions to those identified issues, and present comprehensive information on emerging technologies related to data analytics and complex communication networks such as cloud computing, big data, and IoT. This book will also address different aspects of data analytics and propose novel strategies based on wireless systems and IoT including optimization, control, statistics, social computing, and more. This book is valuable for data scientists, data analysts, network analysts, researchers, academicians, and students interested in the latest developments and advancements in data analytics and complex communication networks.


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