Big data analytics with applications in insider threat detection, Thuraisingham, Bhavani Parveen, Pallabi Masud, Mohammad Mehedy Khan, Latifur
Автор: C.S.R. Prabhu; Aneesh Sreevallabh Chivukula; Adity Название: Big Data Analytics: Systems, Algorithms, Applications ISBN: 9811500932 ISBN-13(EAN): 9789811500930 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Поставка под заказ.
Описание:
This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy.
With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered.
In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition.
Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.
Автор: Raj & Chandra Deka Название: Cloud Infrastructures For Big Data Analytics ISBN: 1466658649 ISBN-13(EAN): 9781466658646 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 50312.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Clouds are being positioned as the next-generation consolidated, centralised, yet federated IT infrastructure for hosting all kinds of IT platforms and for deploying, maintaining, and managing a wider variety of personal, as well as professional, applications and services.Cloud Infrastructures for Big Data Analytics focuses exclusively on the topic of cloud-sponsored big data analytics for creating flexible and futuristic organisations. This book helps researchers and practitioners, as well as business entrepreneurs, to make informed decisions and consider appropriate action to simplify and streamline the arduous journey towards smarter enterprises.
Автор: Anandakumar Haldorai, Arulmurugan Ramu Название: Cognitive Social Mining Applications in Data Analytics and Forensics ISBN: 1522575227 ISBN-13(EAN): 9781522575221 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 28413.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recently, there has been a rapid increase in interest regarding social network analysis in the data mining community. Cognitive radios are expected to play a major role in meeting this exploding traffic demand on social networks due to their ability to sense the environment, analyze outdoor parameters, and then make decisions for dynamic time, frequency, space, resource allocation, and management to improve the utilization of mining the social data.Cognitive Social Mining Applications in Data Analytics and Forensics is an essential reference source that reviews cognitive radio concepts and examines their applications to social mining using a machine learning approach so that an adaptive and intelligent mining is achieved. Featuring research on topics such as data mining, real-time ubiquitous social mining services, and cognitive computing, this book is ideally designed for social network analysts, researchers, academicians, and industry professionals.
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.
Автор: Gunter Wallner Название: Data Analytics Applications in Gaming and Entertainment ISBN: 1138104434 ISBN-13(EAN): 9781138104433 Издательство: Taylor&Francis Рейтинг: Цена: 16078.00 р. Наличие на складе: Поставка под заказ.
Описание: Over the last decade big data and data mining has received growing interest and importance in game production to process and draw actionable insights from large volumes of player-related data in order to inform game design, to ensure customer satisfaction, to maximize revenues, and to drive technical innovation.
Описание: With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools.
Описание: Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution.
Описание: Algorithms and Applications for Academic Search, Recommendation and Quantitative Association Rule Mining presents novel algorithms for academic search, recommendation and association rule mining that have been developed and optimized for different commercial as well as academic purpose systems. Along with the design and implementation of algorithms, a major part of the work presented in the book involves the development of new systems both for commercial as well as for academic use. In the first part of the book the author introduces a novel hierarchical heuristic scheme for re-ranking academic publications retrieved from standard digital libraries. The scheme is based on the hierarchical combination of a custom implementation of the term frequency heuristic, a time-depreciated citation score and a graph-theoretic computed score that relates the paper’s index terms with each other. In order to evaluate the performance of the introduced algorithms, a meta-search engine has been designed and developed that submits user queries to standard digital repositories of academic publications and re-ranks the top-n results using the introduced hierarchical heuristic scheme. In the second part of the book the design of novel recommendation algorithms with application in different types of e-commerce systems are described. The newly introduced algorithms are a part of a developed Movie Recommendation system, the first such system to be commercially deployed in Greece by a major Triple Play services provider. The initial version of the system uses a novel hybrid recommender (user, item and content based) and provides daily recommendations to all active subscribers of the provider (currently more than 30,000). The recommenders that we are presenting are hybrid by nature, using an ensemble configuration of different content, user as well as item-based recommenders in order to provide more accurate recommendation results.The final part of the book presents the design of a quantitative association rule mining algorithm. Quantitative association rules refer to a special type of association rules of the form that antecedent implies consequent consisting of a set of numerical or quantitative attributes. The introduced mining algorithm processes a specific number of user histories in order to generate a set of association rules with a minimally required support and confidence value. The generated rules show strong relationships that exist between the consequent and the antecedent of each rule, representing different items that have been consumed at specific price levels. This research book will be of appeal to researchers, graduate students, professionals, engineers and computer programmers.
Автор: Jason J. Jung; Pankoo Kim; Kwang Nam Choi Название: Big Data Technologies and Applications ISBN: 3319987518 ISBN-13(EAN): 9783319987514 Издательство: Springer Рейтинг: Цена: 5870.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed post-conference proceedings of the 8th International Conference on Big Data Technologies and Applications, BDTA 2017, held in Gwangju, South Korea, in November 2017. The 15 revised full papers were carefully reviewed and selected from 25 submissions and handle theoretical foundations and practical applications which premise the new generation of data analytics and engineering. The contributions deal with following topics: privacy and security, image processing, context awareness, s/w engineering and e-commerce, social media and health care.
Автор: Mehmet Kaya; Jalal Kawash; Suheil Khoury; Min-Yuh Название: Social Network Based Big Data Analysis and Applications ISBN: 3030086399 ISBN-13(EAN): 9783030086398 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book is a timely collection of chapters that present the state of the art within the analysis and application of big data. Working within the broader context of big data, this text focuses on the hot topics of social network modelling and analysis such as online dating recommendations, hiring practices, and subscription-type prediction in mobile phone services. Manuscripts are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM’2016), which was held in August 2016. The papers were among the best featured at the meeting and were then improved and extended substantially. Social Network Based Big Data Analysis and Applications will appeal to students and researchers in the field.
This book addresses the impacts of various types of services such as infrastructure, platforms, software, and business processes that cloud computing and Big Data have introduced into business. Featuring chapters which discuss effective and efficient approaches in dealing with the inherent complexity and increasing demands in data science, a variety of application domains are covered. Various case studies by data management and analysis experts are presented in these chapters. Covered applications include banking, social networks, bioinformatics, healthcare, transportation and criminology. Highlighting the Importance of Big Data Management and Analysis for Various Applications will provide the reader with an understanding of how data management and analysis are adapted to these applications. This book will appeal to researchers and professionals in the field.
Описание: Introduction to Seeing Cities Through Big Data - Research, Methods, and Applications in Urban Informatics.- Big Data and Urban Informatics: Innovations and Challenges to Urban Planning and Knowledge Discovery.- Analytics of user-generated content.- Using User-Generated Content to Understand Cities.- Developing an Interactive Mobile Volunteered Geographic Information Platform to Integrate Environmental Big Data and Citizen Science in Urban Management.- CyberGIS-enabled Urban Sensing from Volunteered Citizen Participation Using Mobile Devices.- Challenges and opportunities of urban Big Data.- The Potential for Big Data to Improve Neighborhood-Level Census Data.- Big Data and Survey Research: Supplement or Substitute?.- Big Spatio-temporal Network Data Analytics for Smart Cities: Research Needs.- A review of heteroscedasticity treatment with Gaussian Processes and Quantile Regression meta-models.- Changing organizational and educational perspectives with urban Big Data.- Urban Informatics: Critical Data and Technology Considerations.- Emerging Urban Digital Infomediaries and Civic Hacking in an Era of Big Data and Open Data Initiatives.- How Should Urban Planners Be Trained to Handle Big Data?.- Energy Planning in Big data Era: A Theme Study of the Residential Sector.- Urban data management.- Using an online spatial analytics workbench for understanding housing affordability in Sydney.- A Big Data Mashing Tool for Measuring Transit System Performance.- Developing a Comprehensive U.S. Transit Accessibility Database.- Seeing Chinese Cities through Big Data and Statistics.- Urban knowledge discovery applied to different urban contexts.- Planning for the Change: Mapping Sea Level Rise and Storm Inundation in Sherman Island Using 3Di Hydrodynamic Model and LiDAR.- The Impact of Land-Use Variables on Free-floating Carsharing Vehicle Rental Choice and Parking Duration.- Dynamic Agent Based Simulation of an Urban Disaster Using Synthetic Big Data.- Estimation of Urban Transport Accessibility at the Spatial Resolution of an Individual Traveler.- Modeling Taxi Demand and Supply in New York City Using Large-Scale Taxi GPS Data.- Detecting stop episodes from GPS trajectories with gaps.- Emergencies and Crisis.- Using Social Media and Satellite Data for Damage Assessment in Urban Areas During Emergencies.- Health and well-being.- 'Big Data': Pedestrian Volume Using Google Street View Images.- Learning from Outdoor Webcams: Surveillance of Physical Activity Across Environments.- Mapping Urban Soundscapes via Citygram.- Social equity and data democracy.- Big Data and Smart (Equitable) Cities.- Big Data, Small Apps: Premises and Products of the Civic Hackathon.
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