December 2, 2020

Download Ebook Free Structured Search For Big Data

Structured Search for Big Data

Structured Search for Big Data
Author : Mikhail Gilula
Publisher : Morgan Kaufmann
Release Date : 2015-08-26
Category : Computers
Total pages :114
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The WWW era made billions of people dramatically dependent on the progress of data technologies, out of which Internet search and Big Data are arguably the most notable. Structured Search paradigm connects them via a fundamental concept of key-objects evolving out of keywords as the units of search. The key-object data model and KeySQL revamp the data independence principle making it applicable for Big Data and complement NoSQL with full-blown structured querying functionality. The ultimate goal is extracting Big Information from the Big Data. As a Big Data Consultant, Mikhail Gilula combines academic background with 20 years of industry experience in the database and data warehousing technologies working as a Sr. Data Architect for Teradata, Alcatel-Lucent, and PayPal, among others. He has authored three books, including The Set Model for Database and Information Systems and holds four US Patents in Structured Search and Data Integration. Conceptualizes structured search as a technology for querying multiple data sources in an independent and scalable manner. Explains how NoSQL and KeySQL complement each other and serve different needs with respect to big data Shows the place of structured search in the internet evolution and describes its implementations including the real-time structured internet search

Structured Search for Big Data: From Keywords to Key-objects

Structured Search for Big Data: From Keywords to Key-objects
Author : Anonim
Publisher : Unknown
Release Date : 2020
Category :
Total pages :129
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Exam Prep for: Structured Search for Big Data

Exam Prep for: Structured Search for Big Data
Author : Anonim
Publisher : Unknown
Release Date : 2020
Category :
Total pages :129
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Big Data in Complex Systems

Big Data in Complex Systems
Author : Aboul Ella Hassanien,Ahmad Taher Azar,Vaclav Snasael,Janusz Kacprzyk,Jemal H. Abawajy
Publisher : Springer
Release Date : 2015-01-02
Category : Technology & Engineering
Total pages :499
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This volume provides challenges and Opportunities with updated, in-depth material on the application of Big data to complex systems in order to find solutions for the challenges and problems facing big data sets applications. Much data today is not natively in structured format; for example, tweets and blogs are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search. Therefore transforming such content into a structured format for later analysis is a major challenge. Data analysis, organization, retrieval, and modeling are other foundational challenges treated in this book. The material of this book will be useful for researchers and practitioners in the field of big data as well as advanced undergraduate and graduate students. Each of the 17 chapters in the book opens with a chapter abstract and key terms list. The chapters are organized along the lines of problem description, related works, and analysis of the results and comparisons are provided whenever feasible.

Big Data Analytics for Large-Scale Multimedia Search

Big Data Analytics for Large-Scale Multimedia Search
Author : Stefanos Vrochidis,Benoit Huet,Edward Y. Chang,Ioannis Kompatsiaris
Publisher : Wiley
Release Date : 2019-05-06
Category : Technology & Engineering
Total pages :376
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A timely overview of cutting edge technologies for multimedia retrieval with a special emphasis on scalability The amount of multimedia data available every day is enormous and is growing at an exponential rate, creating a great need for new and more efficient approaches for large scale multimedia search. This book addresses that need, covering the area of multimedia retrieval and placing a special emphasis on scalability. It reports the recent works in large scale multimedia search, including research methods and applications, and is structured so that readers with basic knowledge can grasp the core message while still allowing experts and specialists to drill further down into the analytical sections. Big Data Analytics for Large-Scale Multimedia Search covers: representation learning, concept and event-based video search in large collections; big data multimedia mining, large scale video understanding, big multimedia data fusion, large-scale social multimedia analysis, privacy and audiovisual content, data storage and management for big multimedia, large scale multimedia search, multimedia tagging using deep learning, interactive interfaces for big multimedia and medical decision support applications using large multimodal data. Addresses the area of multimedia retrieval and pays close attention to the issue of scalability Presents problem driven techniques with solutions that are demonstrated through realistic case studies and user scenarios Includes tables, illustrations, and figures Offers a Wiley-hosted BCS that features links to open source algorithms, data sets and tools Big Data Analytics for Large-Scale Multimedia Search is an excellent book for academics, industrial researchers, and developers interested in big multimedia data search retrieval. It will also appeal to consultants in computer science problems and professionals in the multimedia industry.

Semantic Keyword-Based Search on Structured Data Sources

Semantic Keyword-Based Search on Structured Data Sources
Author : Andrea Calì,Dorian Gorgan,Martín Ugarte
Publisher : Springer
Release Date : 2017-02-13
Category : Computers
Total pages :197
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This book constitutes the thoroughly refereed post-conference proceedings of the Second COST Action IC1302 International KEYSTONE Conference on Semantic Keyword-Based Search on Structured Data Sources, IKC 2016, held in Cluj-Napoca, Romania, in September 2016. The 15 revised full papers and 2 invited papers are reviewed and selected from 18 initial submissions and cover the areas of keyword extraction, natural language searches, graph databases, information retrieval techniques for keyword search and document retrieval.

Social Networks and Questions of Big Data. Graph search for communities with corresponding keywords

Social Networks and Questions of Big Data. Graph search for communities with corresponding keywords
Author : Andrea Attwenger
Publisher : GRIN Verlag
Release Date : 2017-06-27
Category : Computers
Total pages :5
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Seminar paper from the year 2017 in the subject Computer Science - Internet, New Technologies, grade: 1.3, LMU Munich (Institut für Informatik), course: Recent Developments in Data Science, language: English, abstract: This essay deals with a graph search for communities with corresponding keywords. The era of big data and world-spanning social networks has highlighted the necessity of ways to make sense of this vast amount of information. Data can be arranged in a graph of connected vertices, therefore giving it a basic structure. If the vertices are further described by keywords, the structure is called an attributed graph. This paper discusses a query algorithm that scans these attributed graphs for communities that are not only structurally linked - therefore forming subgraphs - but also share the same keywords. This method might give new insights into the composition of large networks, highlight interesting connections and give opportunities for effectively targeted marketing. As a specific use case, the idea of the attributed community query is applied to the example of a film recommendation program.

Big Data of Complex Networks

Big Data of Complex Networks
Author : Matthias Dehmer,Frank Emmert-Streib,Stefan Pickl,Andreas Holzinger
Publisher : CRC Press
Release Date : 2016-08-19
Category : Computers
Total pages :320
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Big Data of Complex Networks presents and explains the methods from the study of big data that can be used in analysing massive structural data sets, including both very large networks and sets of graphs. As well as applying statistical analysis techniques like sampling and bootstrapping in an interdisciplinary manner to produce novel techniques for analyzing massive amounts of data, this book also explores the possibilities offered by the special aspects such as computer memory in investigating large sets of complex networks. Intended for computer scientists, statisticians and mathematicians interested in the big data and networks, Big Data of Complex Networks is also a valuable tool for researchers in the fields of visualization, data analysis, computer vision and bioinformatics. Key features: Provides a complete discussion of both the hardware and software used to organize big data Describes a wide range of useful applications for managing big data and resultant data sets Maintains a firm focus on massive data and large networks Unveils innovative techniques to help readers handle big data Matthias Dehmer received his PhD in computer science from the Darmstadt University of Technology, Germany. Currently, he is Professor at UMIT – The Health and Life Sciences University, Austria, and the Universität der Bundeswehr München. His research interests are in graph theory, data science, complex networks, complexity, statistics and information theory. Frank Emmert-Streib received his PhD in theoretical physics from the University of Bremen, and is currently Associate professor at Tampere University of Technology, Finland. His research interests are in the field of computational biology, machine learning and network medicine. Stefan Pickl holds a PhD in mathematics from the Darmstadt University of Technology, and is currently a Professor at Bundeswehr Universität München. His research interests are in operations research, systems biology, graph theory and discrete optimization. Andreas Holzinger received his PhD in cognitive science from Graz University and his habilitation (second PhD) in computer science from Graz University of Technology. He is head of the Holzinger Group HCI-KDD at the Medical University Graz and Visiting Professor for Machine Learning in Health Informatics Vienna University of Technology.

Enterprise Content and Search Management for Building Digital Platforms

Enterprise Content and Search Management for Building Digital Platforms
Author : Shailesh Kumar Shivakumar
Publisher : John Wiley & Sons
Release Date : 2016-12-16
Category : Computers
Total pages :464
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Provides modern enterprises with the tools to create a robust digital platform utilizing proven best practices, practical models, and time-tested techniques Contemporary business organizations can either embrace the digital revolution—or be left behind. Enterprise Content and Search Management for Building Digital Platforms provides modern enterprises with the necessary tools to create a robust digital platform utilizing proven best practices, practical models, and time-tested techniques to compete in the today’s digital world. Features include comprehensive discussions on content strategy, content key performance indicators (KPIs), mobile-first strategy, content assessment models, various practical techniques and methodologies successfully used in real-world digital programs, relevant case studies, and more. Initial chapters cover core concepts of a content management system (CMS), including content strategy; CMS architecture, templates, and workflow; reference architectures, information architecture, taxonomy, and content metadata. Advanced CMS topics are then covered, with chapters on integration, content standards, digital asset management (DAM), document management, and content migration, evaluation, validation, maintenance, analytics, SEO, security, infrastructure, and performance. The basics of enterprise search technologies are explored next, and address enterprise search architecture, advanced search, operations, and governance. Final chapters then focus on enterprise program management and feature coverage of various concepts of digital program management and best practices—along with an illuminating end-to-end digital program case study. Offers a comprehensive guide to the understanding and learning of new methodologies, techniques, and models for the creation of an end-to-end digital system Addresses a wide variety of proven best practices and deployed techniques in content management and enterprise search space which can be readily used for digital programs Covers the latest digital trends such as mobile-first strategy, responsive design, adaptive content design, micro services architecture, semantic search and such and also utilizes sample reference architecture for implementing solutions Features numerous case studies to enhance comprehension, including a complete end-to-end digital program case study Provides readily usable content management checklists and templates for defining content strategy, CMS evaluation, search evaluation and DAM evaluation Comprehensive and cutting-edge, Enterprise Content and Search Management for Building Digital Platforms is an invaluable reference resource for creating an optimal enterprise digital eco-system to meet the challenges of today’s hyper-connected world.

Big Data in Predictive Toxicology

Big Data in Predictive Toxicology
Author : Andrea-Nicole Richarz,Daniel Neagu
Publisher : Royal Society of Chemistry
Release Date : 2019-12-10
Category : Medical
Total pages :394
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The rate at which toxicological data is generated is continually becoming more rapid and the volume of data generated is growing dramatically. This is due in part to advances in software solutions and cheminformatics approaches which increase the availability of open data from chemical, biological and toxicological and high throughput screening resources. However, the amplified pace and capacity of data generation achieved by these novel techniques presents challenges for organising and analysing data output. Big Data in Predictive Toxicology discusses these challenges as well as the opportunities of new techniques encountered in data science. It addresses the nature of toxicological big data, their storage, analysis and interpretation. It also details how these data can be applied in toxicity prediction, modelling and risk assessment. This title is of particular relevance to researchers and postgraduates working and studying in the fields of computational methods, applied and physical chemistry, cheminformatics, biological sciences, predictive toxicology and safety and hazard assessment.

Data Science and Big Data Analytics

Data Science and Big Data Analytics
Author : EMC Education Services
Publisher : John Wiley & Sons
Release Date : 2015-01-05
Category : Computers
Total pages :432
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Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138. Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!

Modern Big Data Processing with Hadoop

Modern Big Data Processing with Hadoop
Author : V Naresh Kumar,Prashant Shindgikar
Publisher : Packt Publishing Ltd
Release Date : 2018-03-30
Category : Computers
Total pages :394
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A comprehensive guide to design, build and execute effective Big Data strategies using Hadoop Key Features -Get an in-depth view of the Apache Hadoop ecosystem and an overview of the architectural patterns pertaining to the popular Big Data platform -Conquer different data processing and analytics challenges using a multitude of tools such as Apache Spark, Elasticsearch, Tableau and more -A comprehensive, step-by-step guide that will teach you everything you need to know, to be an expert Hadoop Architect Book Description The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools. This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster. By the end of this book, you will have all the knowledge you need to build expert Big Data systems. What you will learn Build an efficient enterprise Big Data strategy centered around Apache Hadoop Gain a thorough understanding of using Hadoop with various Big Data frameworks such as Apache Spark, Elasticsearch and more Set up and deploy your Big Data environment on premises or on the cloud with Apache Ambari Design effective streaming data pipelines and build your own enterprise search solutions Utilize the historical data to build your analytics solutions and visualize them using popular tools such as Apache Superset Plan, set up and administer your Hadoop cluster efficiently Who this book is for This book is for Big Data professionals who want to fast-track their career in the Hadoop industry and become an expert Big Data architect. Project managers and mainframe professionals looking forward to build a career in Big Data Hadoop will also find this book to be useful. Some understanding of Hadoop is required to get the best out of this book.

Semantic Keyword-based Search on Structured Data Sources

Semantic Keyword-based Search on Structured Data Sources
Author : Jorge Cardoso,Francesco Guerra,Geert-Jan Houben,Alexandre Miguel Pinto,Yannis Velegrakis
Publisher : Springer
Release Date : 2016-01-06
Category : Computers
Total pages :209
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This book constitutes the thoroughly refereed post-conference proceedings of the First COST Action IC1302 International KEYSTONE Conference on semantic Keyword-based Search on Structured Data Sources, IKC 2015, held in Coimbra, Portugal, in September 2015. The 13 revised full papers, 3 revised short papers, and 2 invited papers were carefully reviewed and selected from 22 initial submissions. The paper topics cover techniques for keyword search, semantic data management, social Web and social media, information retrieval, benchmarking for search on big data.

Big Data, Big Analytics

Big Data, Big Analytics
Author : Michael Minelli,Michele Chambers,Ambiga Dhiraj
Publisher : John Wiley & Sons
Release Date : 2012-12-27
Category : Business & Economics
Total pages :224
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Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.

Splunk Software: Guide to Splunk for Beginner: Big Data ...

Splunk Software: Guide to Splunk for Beginner: Big Data ...
Author : Anonim
Publisher : Unknown
Release Date : 2020
Category :
Total pages :129
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