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Author: Ihab F. Ilyas Publisher: Morgan & Claypool ISBN: 1450371558 Category : Computers Languages : en Pages : 282
Book Description
Data quality is one of the most important problems in data management, since dirty data often leads to inaccurate data analytics results and incorrect business decisions. Poor data across businesses and the U.S. government are reported to cost trillions of dollars a year. Multiple surveys show that dirty data is the most common barrier faced by data scientists. Not surprisingly, developing effective and efficient data cleaning solutions is challenging and is rife with deep theoretical and engineering problems. This book is about data cleaning, which is used to refer to all kinds of tasks and activities to detect and repair errors in the data. Rather than focus on a particular data cleaning task, we give an overview of the end-to-end data cleaning process, describing various error detection and repair methods, and attempt to anchor these proposals with multiple taxonomies and views. Specifically, we cover four of the most common and important data cleaning tasks, namely, outlier detection, data transformation, error repair (including imputing missing values), and data deduplication. Furthermore, due to the increasing popularity and applicability of machine learning techniques, we include a chapter that specifically explores how machine learning techniques are used for data cleaning, and how data cleaning is used to improve machine learning models. This book is intended to serve as a useful reference for researchers and practitioners who are interested in the area of data quality and data cleaning. It can also be used as a textbook for a graduate course. Although we aim at covering state-of-the-art algorithms and techniques, we recognize that data cleaning is still an active field of research and therefore provide future directions of research whenever appropriate.
Author: Ihab F. Ilyas Publisher: Morgan & Claypool ISBN: 1450371558 Category : Computers Languages : en Pages : 282
Book Description
Data quality is one of the most important problems in data management, since dirty data often leads to inaccurate data analytics results and incorrect business decisions. Poor data across businesses and the U.S. government are reported to cost trillions of dollars a year. Multiple surveys show that dirty data is the most common barrier faced by data scientists. Not surprisingly, developing effective and efficient data cleaning solutions is challenging and is rife with deep theoretical and engineering problems. This book is about data cleaning, which is used to refer to all kinds of tasks and activities to detect and repair errors in the data. Rather than focus on a particular data cleaning task, we give an overview of the end-to-end data cleaning process, describing various error detection and repair methods, and attempt to anchor these proposals with multiple taxonomies and views. Specifically, we cover four of the most common and important data cleaning tasks, namely, outlier detection, data transformation, error repair (including imputing missing values), and data deduplication. Furthermore, due to the increasing popularity and applicability of machine learning techniques, we include a chapter that specifically explores how machine learning techniques are used for data cleaning, and how data cleaning is used to improve machine learning models. This book is intended to serve as a useful reference for researchers and practitioners who are interested in the area of data quality and data cleaning. It can also be used as a textbook for a graduate course. Although we aim at covering state-of-the-art algorithms and techniques, we recognize that data cleaning is still an active field of research and therefore provide future directions of research whenever appropriate.
Author: Basant Agarwal Publisher: Academic Press ISBN: 0128190620 Category : Science Languages : en Pages : 367
Book Description
Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they are applied to Biomedical Engineering, Electronic Health Records, and medical image processing. Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including Deep Learning for drug discovery, clinical decision support systems, disease diagnosis, prediction and monitoring Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis
Author: Ngoc Thanh Nguyen Publisher: Springer ISBN: 3319902873 Category : Computers Languages : en Pages : 210
Book Description
These transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the semantic Web, social networks, and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies, such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems. This twenty-ninth issue is a regular issue with 10 selected papers.
Author: Tran Khanh Dang Publisher: Springer Nature ISBN: 9813343702 Category : Computers Languages : en Pages : 499
Book Description
This book constitutes the proceedings of the 7th International Conference on Future Data and Security Engineering, FDSE 2020, held in Quy Nhon, Vietnam, in November 2020.* The 29 full papers and 8 short were carefully reviewed and selected from 161 submissions. The selected papers are organized into the following topical headings: big data analytics and distributed systems; security and privacy engineering; industry 4.0 and smart city: data analytics and security; data analytics and healthcare systems; machine learning-based big data processing; emerging data management systems and applications; and short papers: security and data engineering. * The conference was held virtually due to the COVID-19 pandemic.
Author: Alex Petrov Publisher: O'Reilly Media ISBN: 1492040312 Category : Computers Languages : en Pages : 373
Book Description
When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it’s often difficult to understand what each one offers and how they differ. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals. Throughout the book, you’ll explore relevant material gleaned from numerous books, papers, blog posts, and the source code of several open source databases. These resources are listed at the end of parts one and two. You’ll discover that the most significant distinctions among many modern databases reside in subsystems that determine how storage is organized and how data is distributed. This book examines: Storage engines: Explore storage classification and taxonomy, and dive into B-Tree-based and immutable Log Structured storage engines, with differences and use-cases for each Storage building blocks: Learn how database files are organized to build efficient storage, using auxiliary data structures such as Page Cache, Buffer Pool and Write-Ahead Log Distributed systems: Learn step-by-step how nodes and processes connect and build complex communication patterns Database clusters: Which consistency models are commonly used by modern databases and how distributed storage systems achieve consistency
Author: Sridhar, Varadharajan Publisher: IGI Global ISBN: 1466620277 Category : Computers Languages : en Pages : 356
Book Description
"This book highlights comprehensive research that will enable readers to understand, manage, use, and maintain business data communication networks more effectively"--Provided by publisher.
Author: Qilian Liang Publisher: Springer Nature ISBN: 9811584117 Category : Technology & Engineering Languages : en Pages : 2070
Book Description
This book brings together papers presented at the 2020 International Conference on Communications, Signal Processing, and Systems, which provides a venue to disseminate the latest developments and to discuss the interactions and links between these multidisciplinary fields. Spanning topics ranging from communications, signal processing and systems, this book is aimed at undergraduate and graduate students in Electrical Engineering, Computer Science and Mathematics, researchers and engineers from academia and industry as well as government employees (such as NSF, DOD and DOE).
Author: Ramesh Subramanian Publisher: IGI Global ISBN: 1591404312 Category : Computers Languages : en Pages : 308
Book Description
Peer to Peer Computing: The Evolution of a Disruptive Technology takes a holistic approach to the affects P2P Computing has on a number a disciplines. Some of those areas covered within this book include grid computing, web services, bioinformatics, security, finance and economics, collaboration, and legal issues. Unique in its approach, Peer to Peer Computing includes current articles from academics as well as IT practitioners and consultants from around the world. As a result, the book strikes a balance for many readers. Neither too technical or too managerial, Peer to Peer Computing appeals to the needs of both researchers and practitioners who are trying to gain a more thorough understanding of current P2P technologies and their emerging ramifications.
Author: G. Jezic Publisher: Springer Nature ISBN: 9811629943 Category : Technology & Engineering Languages : en Pages : 509
Book Description
This book highlights new trends and challenges in research on agents and the new digital and knowledge economy. It includes papers on business process management, agent-based modeling and simulation, and anthropic-oriented computing that were originally presented at the 15th International KES Conference on Agents and Multi-Agent Systems: Technologies and Applications (KES-AMSTA 2021), being held as a Virtual Conference in June 14–16, 2021. The respective papers cover topics such as software agents, multi-agent systems, agent modeling, mobile and cloud computing, big data analysis, business intelligence, artificial intelligence, social systems, computer embedded systems, and nature-inspired manufacturing, all of which contribute to the modern digital economy.
Author: Ruay-Shiung Chang Publisher: Springer Science & Business Media ISBN: 3642354521 Category : Technology & Engineering Languages : en Pages : 721
Book Description
The field of Intelligent Systems and Applications has expanded enormously during the last two decades. Theoretical and practical results in this area are growing rapidly due to many successful applications and new theories derived from many diverse problems. This book is dedicated to the Intelligent Systems and Applications in many different aspects. In particular, this book is to provide highlights of the current research in Intelligent Systems and Applications. It consists of research papers in the following specific topics: l Graph Theory and Algorithms l Interconnection Networks and Combinatorial Algorithms l Artificial Intelligence and Fuzzy Systems l Database, Data Mining, and Information Retrieval l Information Literacy, e-Learning, and Social Media l Computer Networks and Web Service/Technologies l Wireless Sensor Networks l Wireless Network Protocols l Wireless Data Processing This book provides a reference to theoretical problems as well as practical solutions and applications for the state-of-the-art results in Intelligent Systems and Applications on the aforementioned topics. In particular, both the academic community (graduate students, post-doctors and faculties) in Electrical Engineering, Computer Science, and Applied Mathematics; and the industrial community (engineers, engineering managers, programmers, research lab staffs and managers, security managers) will find this book interesting.
Author: Ihab F. Ilyas
Author: Ihab F. Ilyas
Author: Basant Agarwal
Author: Ngoc Thanh Nguyen
Author: Tran Khanh Dang
Author: Alex Petrov
Author: Sridhar, Varadharajan
Author: Qilian Liang
Author: Ramesh Subramanian
Author: G. Jezic
Author: Ruay-Shiung Chang