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Author: Peter Christen
Publisher: Springer Science & Business Media
ISBN: 3642311644
Category : Computers
Languages : en
Pages : 279
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Book Description
Data matching (also known as record or data linkage, entity resolution, object identification, or field matching) is the task of identifying, matching and merging records that correspond to the same entities from several databases or even within one database. Based on research in various domains including applied statistics, health informatics, data mining, machine learning, artificial intelligence, database management, and digital libraries, significant advances have been achieved over the last decade in all aspects of the data matching process, especially on how to improve the accuracy of data matching, and its scalability to large databases. Peter Christen’s book is divided into three parts: Part I, “Overview”, introduces the subject by presenting several sample applications and their special challenges, as well as a general overview of a generic data matching process. Part II, “Steps of the Data Matching Process”, then details its main steps like pre-processing, indexing, field and record comparison, classification, and quality evaluation. Lastly, part III, “Further Topics”, deals with specific aspects like privacy, real-time matching, or matching unstructured data. Finally, it briefly describes the main features of many research and open source systems available today. By providing the reader with a broad range of data matching concepts and techniques and touching on all aspects of the data matching process, this book helps researchers as well as students specializing in data quality or data matching aspects to familiarize themselves with recent research advances and to identify open research challenges in the area of data matching. To this end, each chapter of the book includes a final section that provides pointers to further background and research material. Practitioners will better understand the current state of the art in data matching as well as the internal workings and limitations of current systems. Especially, they will learn that it is often not feasible to simply implement an existing off-the-shelf data matching system without substantial adaption and customization. Such practical considerations are discussed for each of the major steps in the data matching process.
Author: Peter Christen
Publisher: Springer Science & Business Media
ISBN: 3642311644
Category : Computers
Languages : en
Pages : 279
Get Book Here
Book Description
Data matching (also known as record or data linkage, entity resolution, object identification, or field matching) is the task of identifying, matching and merging records that correspond to the same entities from several databases or even within one database. Based on research in various domains including applied statistics, health informatics, data mining, machine learning, artificial intelligence, database management, and digital libraries, significant advances have been achieved over the last decade in all aspects of the data matching process, especially on how to improve the accuracy of data matching, and its scalability to large databases. Peter Christen’s book is divided into three parts: Part I, “Overview”, introduces the subject by presenting several sample applications and their special challenges, as well as a general overview of a generic data matching process. Part II, “Steps of the Data Matching Process”, then details its main steps like pre-processing, indexing, field and record comparison, classification, and quality evaluation. Lastly, part III, “Further Topics”, deals with specific aspects like privacy, real-time matching, or matching unstructured data. Finally, it briefly describes the main features of many research and open source systems available today. By providing the reader with a broad range of data matching concepts and techniques and touching on all aspects of the data matching process, this book helps researchers as well as students specializing in data quality or data matching aspects to familiarize themselves with recent research advances and to identify open research challenges in the area of data matching. To this end, each chapter of the book includes a final section that provides pointers to further background and research material. Practitioners will better understand the current state of the art in data matching as well as the internal workings and limitations of current systems. Especially, they will learn that it is often not feasible to simply implement an existing off-the-shelf data matching system without substantial adaption and customization. Such practical considerations are discussed for each of the major steps in the data matching process.
Author: Jill Dunlap Brown
Publisher: Routledge
ISBN: 1000586715
Category : Education
Languages : en
Pages : 130
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Book Description
This accessible and reader-friendly book will help you assess and determine the foundational reading needs of each of your K – 5 students. Literacy leaders Jill Dunlap Brown and Jana Schmidt offer an easy-to-use data analysis tool called, "The Columns" for teachers at all levels of experience to make sense of classroom data for elementary readers. This book will guide you in using the tool to identify the root causes of foundational reading deficits and to plan appropriate interventions. Sample case studies allow you to practice identifying needs and matching interventions. Stories and examples throughout the book will encourage you as you help your students meet their full potential. The book provides easy-to-use and printable versions of the data analysis columns that will enable you to put the authors‘ advice into immediate action. These tools are available for download on the book’s product page: www.routledge.com/9780367225070
Author:
Publisher:
ISBN:
Category : Student financial aid administration
Languages : en
Pages : 168
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Book Description
Author: Jim Lehmer
Publisher: "O'Reilly Media, Inc."
ISBN: 1098152247
Category : Computers
Languages : en
Pages : 285
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Book Description
If you were handed two different but related sets of data, what tools would you use to find the matches? What if all you had was SQL SELECT access to a database? In this practical book, author Jim Lehmer provides best practices, techniques, and tricks to help you import, clean, match, score, and think about heterogeneous data using SQL. DBAs, programmers, business analysts, and data scientists will learn how to identify and remove duplicates, parse strings, extract data from XML and JSON, generate SQL using SQL, regularize data and prepare datasets, and apply data quality and ETL approaches for finding the similarities and differences between various expressions of the same data. Full of real-world techniques, the examples in the book contain working code. You'll learn how to: Identity and remove duplicates in two different datasets using SQL Regularize data and achieve data quality using SQL Extract data from XML and JSON Generate SQL using SQL to increase your productivity Prepare datasets for import, merging, and better analysis using SQL Report results using SQL Apply data quality and ETL approaches to finding similarities and differences between various expressions of the same data
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 168
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Book Description
Author:
Publisher:
ISBN:
Category : Student financial aid administration
Languages : en
Pages : 52
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Book Description
Author: United States. Congress. House. Committee on Ways and Means. Subcommittee on Human Resources
Publisher:
ISBN:
Category : Family services
Languages : en
Pages : 96
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Book Description
Author: Susanne Rässler
Publisher: Springer Science & Business Media
ISBN: 1461300533
Category : Mathematics
Languages : en
Pages : 260
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Book Description
Government policy questions and media planning tasks may be answered by this data set. It covers a wide range of different aspects of statistical matching that in Europe typically is called data fusion. A book about statistical matching will be of interest to researchers and practitioners, starting with data collection and the production of public use micro files, data banks, and data bases. People in the areas of database marketing, public health analysis, socioeconomic modeling, and official statistics will find it useful.
Author: Zohra Bellahsene
Publisher: Springer Science & Business Media
ISBN: 3642165184
Category : Computers
Languages : en
Pages : 326
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Book Description
Requiring heterogeneous information systems to cooperate and communicate has now become crucial, especially in application areas like e-business, Web-based mash-ups and the life sciences. Such cooperating systems have to automatically and efficiently match, exchange, transform and integrate large data sets from different sources and of different structure in order to enable seamless data exchange and transformation. The book edited by Bellahsene, Bonifati and Rahm provides an overview of the ways in which the schema and ontology matching and mapping tools have addressed the above requirements and points to the open technical challenges. The contributions from leading experts are structured into three parts: large-scale and knowledge-driven schema matching, quality-driven schema mapping and evolution, and evaluation and tuning of matching tasks. The authors describe the state of the art by discussing the latest achievements such as more effective methods for matching data, mapping transformation verification, adaptation to the context and size of the matching and mapping tasks, mapping-driven schema evolution and merging, and mapping evaluation and tuning. The overall result is a coherent, comprehensive picture of the field. With this book, the editors introduce graduate students and advanced professionals to this exciting field. For researchers, they provide an up-to-date source of reference about schema and ontology matching, schema and ontology evolution, and schema merging.
Author: Amy Webb
Publisher: Penguin
ISBN: 0142180459
Category : Biography & Autobiography
Languages : en
Pages : 306
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Book Description
“Amy Webb found her true love after a search that's both charmingly romantic and relentlessly data-driven. Anyone who uses online dating sites must read her funny, fascinating book.”—Gretchen Rubin, #1 New York Times bestselling author of The Happiness Project After yet another disastrous date, Amy Webb was preparing to cancel her JDate membership when epiphany struck: her standards weren’t too high, she just wasn’t approaching the process the right way. Using her gift for data strategy, she found which keywords were digital-man magnets, analyzed photos, and then adjusted her (female) profile to make the most of that intel. Then began the deluge—dozens of men who actually met her own stringent requirements wanted to meet her. Among them: her future husband, now the father of her child.
