Isbn: 9783642311635 - data matching: concepts and techniques for record linkage, entity resolution, and duplicate detection (data-centric systems and applications) (15 resultados)

Condición: good. Book shows general signs of use and handling. May have light wear on the cover or edges and minimal writing or highlighting. Binding remains tight, and pages are clean and readable.

hardcover. Condición: Very Good. Most items will be dispatched the same or the next working day. A copy that has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

hardcover. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Paperback. Condición: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Hardcover. Condición: new. New Copy. Customer Service Guaranteed.

Hardcover. Condición: Brand New. 2012 edition. 289 pages. 9.75x6.50x0.75 inches. In Stock.

Condición: New. A brand new book in pristine condition. Showing zero signs of shelf wear, creases, or damage.

Condición: New. pp. 292 Index.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…

Condición: new. Questo è un articolo print on demand.

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 292 pp. Englisch.…

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. First book on a topic of growing importance for applications Brings together research from various areas like databases, statistics, information retrieval, data mining, and machine learningDetails the data matching process step by step.…

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 292 pp. Englisch.…

Condición: New. Print on Demand pp. 292 66 Illus.

Condición: New. PRINT ON DEMAND pp. 292.