Data Matching: Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection (Data-Centric Systems and Applications)
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. Search and download Data Matching: Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection (Data-Centric Systems and Applications) for free. Download Data Matching: Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection (Data-Centric Systems and Applications) and other books from rapidshare mediafire.
Data Matching SPRNC 9783642311635 09783642311635 Find new edition of Data Matching here
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.
Data Matching: Concepts And Techniques For Record Linkage, Entity Resolution, An
author peter christen format hardback language english publication year 05 07 2012 series data centric systems and applications subject computing it subject 2 computing professional programming title data matching concepts and techniques for record linkage entity resolution and duplicate detection author christen peter publisher springer verlag new york inc publication date aug 28 2012 pages 289 binding hardcover edition 2012 dimensions 6 50 wx 9 75 hx 0 75 d isbn 3642311636 subject computers
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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 da
author peter christen format hardback language english publication year 05 07 2012 series data centric systems and applications subject computing it subject 2 computing professional programming author biography peter christen is senior lecturer at the research school of computer science at the australian national university in canberra australia his research interests are data mining with a focus on data matching and privacy preserving data sharing and mining he has published over 50 papers in t
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Peter Christen's book is divided into three parts: Part I, "Overview", introduces the subject
