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Author: Ripon Patgiri
Publisher: Academic Press
ISBN: 0128236469
Category : Science
Languages : en
Pages : 230
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Book Description
Bloom Filter: A Data Structure for Computer Networking, Big Data, Cloud Computing, Internet of Things, Bioinformatics, and Beyond focuses on both the theory and practice of the most emerging areas for Bloom filter application, including Big Data, Cloud Computing, Internet of Things, and Bioinformatics. Sections provide in-depth insights on structure and variants, focus on its role in computer networking, and discuss applications in various research domains, such as Big Data, Cloud Computing, and Bioinformatics. Since its inception, the Bloom Filter has been extensively experimented with and developed to enhance system performance such as web cache. Bloom filter influences many research fields, including Bioinformatics, Internet of Things, computer security, network appliances, Big Data and Cloud Computing. - Includes Bloom filter methods for a wide variety of applications - Defines concepts and implementation strategies that will help the reader use the suggested methods - Provides an overview of issues and challenges faced by researchers
Author: Ripon Patgiri
Publisher: Academic Press
ISBN: 0128236469
Category : Science
Languages : en
Pages : 230
Get Book Here
Book Description
Bloom Filter: A Data Structure for Computer Networking, Big Data, Cloud Computing, Internet of Things, Bioinformatics, and Beyond focuses on both the theory and practice of the most emerging areas for Bloom filter application, including Big Data, Cloud Computing, Internet of Things, and Bioinformatics. Sections provide in-depth insights on structure and variants, focus on its role in computer networking, and discuss applications in various research domains, such as Big Data, Cloud Computing, and Bioinformatics. Since its inception, the Bloom Filter has been extensively experimented with and developed to enhance system performance such as web cache. Bloom filter influences many research fields, including Bioinformatics, Internet of Things, computer security, network appliances, Big Data and Cloud Computing. - Includes Bloom filter methods for a wide variety of applications - Defines concepts and implementation strategies that will help the reader use the suggested methods - Provides an overview of issues and challenges faced by researchers
Author: Bryan O'Sullivan
Publisher: "O'Reilly Media, Inc."
ISBN: 0596554303
Category : Computers
Languages : en
Pages : 714
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Book Description
This easy-to-use, fast-moving tutorial introduces you to functional programming with Haskell. You'll learn how to use Haskell in a variety of practical ways, from short scripts to large and demanding applications. Real World Haskell takes you through the basics of functional programming at a brisk pace, and then helps you increase your understanding of Haskell in real-world issues like I/O, performance, dealing with data, concurrency, and more as you move through each chapter.
Author: Mahmoud Parsian
Publisher: "O'Reilly Media, Inc."
ISBN: 1491906154
Category : Computers
Languages : en
Pages : 778
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Book Description
If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as building a recommendation system. You’ll learn how to implement the appropriate MapReduce solution with code that you can use in your projects. Dr. Mahmoud Parsian covers basic design patterns, optimization techniques, and data mining and machine learning solutions for problems in bioinformatics, genomics, statistics, and social network analysis. This book also includes an overview of MapReduce, Hadoop, and Spark. Topics include: Market basket analysis for a large set of transactions Data mining algorithms (K-means, KNN, and Naive Bayes) Using huge genomic data to sequence DNA and RNA Naive Bayes theorem and Markov chains for data and market prediction Recommendation algorithms and pairwise document similarity Linear regression, Cox regression, and Pearson correlation Allelic frequency and mining DNA Social network analysis (recommendation systems, counting triangles, sentiment analysis)
Author: Peter Christen
Publisher:
ISBN: 3030597067
Category : Computer security
Languages : en
Pages : 476
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Book Description
This book provides modern technical answers to the legal requirements of pseudonymisation as recommended by privacy legislation. It covers topics such as modern regulatory frameworks for sharing and linking sensitive information, concepts and algorithms for privacy-preserving record linkage and their computational aspects, practical considerations such as dealing with dirty and missing data, as well as privacy, risk, and performance assessment measures. Existing techniques for privacy-preserving record linkage are evaluated empirically and real-world application examples that scale to population sizes are described. The book also includes pointers to freely available software tools, benchmark data sets, and tools to generate synthetic data that can be used to test and evaluate linkage techniques. This book consists of fourteen chapters grouped into four parts, and two appendices. The first part introduces the reader to the topic of linking sensitive data, the second part covers methods and techniques to link such data, the third part discusses aspects of practical importance, and the fourth part provides an outlook of future challenges and open research problems relevant to linking sensitive databases. The appendices provide pointers and describe freely available, open-source software systems that allow the linkage of sensitive data, and provide further details about the evaluations presented. A companion Web site at https://dmm.anu.edu.au/lsdbook2020 provides additional material and Python programs used in the book. This book is mainly written for applied scientists, researchers, and advanced practitioners in governments, industry, and universities who are concerned with developing, implementing, and deploying systems and tools to share sensitive information in administrative, commercial, or medical databases. The Book describes how linkage methods work and how to evaluate their performance. It covers all the major concepts and methods and also discusses practical matters such as computational efficiency, which are critical if the methods are to be used in practice - and it does all this in a highly accessible way! David J. Hand, Imperial College, London.
Author: Dzejla Medjedovic
Publisher: Simon and Schuster
ISBN: 1638356564
Category : Computers
Languages : en
Pages : 302
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Book Description
Massive modern datasets make traditional data structures and algorithms grind to a halt. This fun and practical guide introduces cutting-edge techniques that can reliably handle even the largest distributed datasets. In Algorithms and Data Structures for Massive Datasets you will learn: Probabilistic sketching data structures for practical problems Choosing the right database engine for your application Evaluating and designing efficient on-disk data structures and algorithms Understanding the algorithmic trade-offs involved in massive-scale systems Deriving basic statistics from streaming data Correctly sampling streaming data Computing percentiles with limited space resources Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You’ll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data. These effective techniques can be applied to any discipline, from finance to text analysis. Graphics, illustrations, and hands-on industry examples make complex ideas practical to implement in your projects—and there’s no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and you’ll find the sweet spot of saving space without sacrificing your data’s accuracy. About the technology Standard algorithms and data structures may become slow—or fail altogether—when applied to large distributed datasets. Choosing algorithms designed for big data saves time, increases accuracy, and reduces processing cost. This unique book distills cutting-edge research papers into practical techniques for sketching, streaming, and organizing massive datasets on-disk and in the cloud. About the book Algorithms and Data Structures for Massive Datasets introduces processing and analytics techniques for large distributed data. Packed with industry stories and entertaining illustrations, this friendly guide makes even complex concepts easy to understand. You’ll explore real-world examples as you learn to map powerful algorithms like Bloom filters, Count-min sketch, HyperLogLog, and LSM-trees to your own use cases. What's inside Probabilistic sketching data structures Choosing the right database engine Designing efficient on-disk data structures and algorithms Algorithmic tradeoffs in massive-scale systems Computing percentiles with limited space resources About the reader Examples in Python, R, and pseudocode. About the author Dzejla Medjedovic earned her PhD in the Applied Algorithms Lab at Stony Brook University, New York. Emin Tahirovic earned his PhD in biostatistics from University of Pennsylvania. Illustrator Ines Dedovic earned her PhD at the Institute for Imaging and Computer Vision at RWTH Aachen University, Germany. Table of Contents 1 Introduction PART 1 HASH-BASED SKETCHES 2 Review of hash tables and modern hashing 3 Approximate membership: Bloom and quotient filters 4 Frequency estimation and count-min sketch 5 Cardinality estimation and HyperLogLog PART 2 REAL-TIME ANALYTICS 6 Streaming data: Bringing everything together 7 Sampling from data streams 8 Approximate quantiles on data streams PART 3 DATA STRUCTURES FOR DATABASES AND EXTERNAL MEMORY ALGORITHMS 9 Introducing the external memory model 10 Data structures for databases: B-trees, Bε-trees, and LSM-trees 11 External memory sorting
Author: Tsuyoshi Takagi
Publisher: Springer
ISBN: 3642332722
Category : Computers
Languages : en
Pages : 347
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Book Description
This book constitutes the refereed proceedings of the 6th International Conference on Provable Security, ProvSec 2012, held in Chengdu, China, in September 2012. The 16 full papers and 4 short papers presented were carefully reviewed and selected from 66 submissions. The papers are grouped in topical sections on signature schemes, foundations, leakage resilence and key escrow, encryption schemes, and information theoretical security.
Author: Michael Gerndt
Publisher: Springer Science & Business Media
ISBN: 3540393684
Category : Computers
Languages : en
Pages : 960
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Book Description
This book constitutes the refereed proceedings of the Second International Conference on High Performance Computing and Communications, HPCC 2006. The book presents 95 revised full papers, addressing all current issues of parallel and distributed systems and high performance computing and communication. Coverage includes networking protocols, routing, and algorithms, languages and compilers for HPC, parallel and distributed architectures and algorithms, wireless, mobile and pervasive computing, Web services, peer-to-peer computing, and more.
Author: Qi Luo
Publisher: Springer Science & Business Media
ISBN: 3642023428
Category : Computers
Languages : en
Pages : 260
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Book Description
The International Conference on Future Computer and Communication was held in Wuhan, China, June 6–7, 2009. The following topics are covered by FCC Conference: agents, knowledge-based technologies, bioinformatics engineering, computer architecture and design, computer networks and security, data mining and database applications, high-performance networks and protocols, multimedia and web services, network reliability and QoS, neural networks and intelligent systems, software engineering and agile development, antennas and propagation, information theory and coding, multiple access techniques, optical communications and photonics, RF and microwave devices, satellite, space and wireless communications, signal and image processing, 3G, 4G mobile communications, communications IC Design, instrumentation and control, and VLSI design. The purpose of the FCC conferences is to bring together researchers and practitioners from academia, industry, and government to exchange their research ideas and results and to discuss the state of the art in the areas covered by the conference The conference included invited talks, workshops, tutorials, and other events dedicated to this area. FCC 2009 provided a forum for engineers and scientists in academia, university and industry to present their latest research findings in any aspects of future computers and communication. The conference was co-sponsored by the Engineering Technology Press, Hong Kong, IEEE SMC TC on Education Technology and Training, and the Intelligent Information Technology Application Research Association, Hong Kong. Much work went into preparing a program of high quality. We received 110 submissions.
Author: Shui Yu
Publisher: Springer Nature
ISBN: 3031334582
Category : Computers
Languages : en
Pages : 169
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Book Description
This book constitutes the refereed post-conference proceedings of the 17th EAI International Conference on Tools for Design, Implementation and Verification of Emerging Information Technologies, TridentCom 2022, which was held in Melbourne, Australia, in November 23-25,2022. The 11 full papers were selected from 30 submissions and deal the emerging technologies of big data, cyber-physical systems and computer communications. The papers are grouped in thematical sessions on network security; network communication; network services; mobile and ad hoc networks; blockchain; machine learning.
Author: Donald Miner
Publisher: "O'Reilly Media, Inc."
ISBN: 1449358551
Category :
Languages : en
Pages : 252
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Book Description
