Kategoria BISAC: Computers >> Data Science - Data Analytics

This book constitutes the refereed proceedings of the Second International Conference on Cloud Computing and Big Data, CloudCom-Asia 2015, held in Huangshan, China, in June 2015.

The 29 full papers and two keynote speeches were carefully reviewed and selected from 106 submissions. The papers are organized in topical sections on cloud architecture; applications; big data and social network; security and privacy.

Learn the right cutting-edge skills and knowledge to leverage Spark Streaming to implement a wide array of real-time, streaming applications. This book walks you through end-to-end real-time application development using real-world applications, data, and code. Taking an application-first approach, each chapter introduces use cases from a specific industry and uses publicly available datasets from that domain to unravel the intricacies of production-grade design and implementation. The domains covered in Pro Spark Streaming include social media, the sharing economy, finance,...

This book introduces Meaningful Purposive Interaction Analysis (MPIA) theory, which combines social network analysis (SNA) with latent semantic analysis (LSA) to help create and analyse a meaningful learning landscape from the digital traces left by a learning community in the co-construction of knowledge.

The hybrid algorithm is implemented in the statistical programming language and environment R, introducing packages which capture through matrix algebra elements of learners work with more knowledgeable others and resourceful content artefacts. The book provides comprehensive...

This book covers the major fundamentals of and the latest research on next-generation spatio-temporal recommendation systems in social media. It begins by describing the emerging characteristics of social media in the era of mobile internet, and explores the limitations to be found in current recommender techniques. The book subsequently presents a series of latent-class user models to simulate users' behaviors in decision-making processes, which effectively overcome the challenges arising from temporal dynamics of users' behaviors, user interest drift over geographical regions, data...

This work presents link prediction similarity measures for social networks that exploit the degree distribution of the networks. In the context of link prediction in dense networks, the text proposes similarity measures based on Markov inequality degree thresholding (MIDTs), which only consider nodes whose degree is above a threshold for a possible link. Also presented are similarity measures based on cliques (CNC, AAC, RAC), which assign extra weight between nodes sharing a greater number of cliques. Additionally, a locally adaptive (LA) similarity measure is proposed that assigns...

This book constitutes the thoroughly revised selected papers of the 6th workshop on Big Data Benchmarks, Performance Optimization, and Emerging Hardware, BPOE 2015, held in Kohala Coast, HI, USA, in August/September 2015 as satellite event of VLDB 2015, the 41st International Conference on Very Large Data Bases.

This textbook provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. These embrace the family of neural networks, fuzzy systems and evolutionary computing in addition to other fields within machine learning, and will help in identifying, visualizing, classifying and analyzing data to support business decisions./p>

The authors, discuss advantages and drawbacks of different approaches, and present a sound foundation for the reader to design and implement data analytic solutions for real‐world applications in an...

This book constitutes the refereed proceedings of the First National Conference on Big Data Technology and Applications, BDTA 2015, held in Harbin, China, in December 2015.

The 26 revised papers presented were carefully reviewed and selected from numerous submissions. The papers address issues such as the storage technology of Big Data; analysis of Big Data and data mining; visualization of Big Data; the parallel computing framework under Big Data; the architecture and basic theory of Big Data; collection and preprocessing of Big Data; innovative applications in some areas,...

Data Simplification: Taming Information With Open Source Tools addresses the simple fact that modern data is too big and complex to analyze in its native form. Data simplification is the process whereby large and complex data is rendered usable. Complex data must be simplified before it can be analyzed, but the process of data simplification is anything but simple, requiring a specialized set of skills and tools.

This book provides data scientists from every scientific discipline with the methods and tools to simplify their data for immediate analysis or long-term...

Microsoft Azure has over 20 platform-as-a-service (PaaS) offerings that can act in support of a big data analytics solution. So which one is right for your project? This practical book helps you understand the breadth of Azure services by organizing them into a reference framework you can use when crafting your own big data analytics solution.

You'll not only be able to determine which service best fits the job, but also learn how to implement a complete solution that scales, provides human fault tolerance, and supports future needs.

• Understand the fundamental patterns of...

Formative Assessment, Learning Data Analytics and Gamification: An ICT Education discusses the challenges associated with assessing student progress given the explosion of e-learning environments, such as MOOCs and online courses that incorporate activities such as design and modeling. This book shows educators how to effectively garner intelligent data from online educational environments that combine assessment and gamification.

This data, when used effectively, can have a positive impact on learning environments and be used for building learner profiles, community...

Pervasive Computing: Next Generation Platforms for Intelligent Data Collection presents current advances and state-of-the-art work on methods, techniques, and algorithms designed to support pervasive collection of data under ubiquitous networks of devices able to intelligently collaborate towards common goals.

Using numerous illustrative examples and following both theoretical and practical results the authors discuss: a coherent and realistic image of today's architectures, techniques, protocols, components, orchestration, choreography, and developments related to pervasive...