An Introduction to Duplicate Detection (Record no. 85305)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03506nam a22005055i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-031-01835-0 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240730164114.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 220601s2010 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783031018350 |
| -- | 978-3-031-01835-0 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 004.6 |
| 100 1# - AUTHOR NAME | |
| Author | Nauman, Felix. |
| 245 13 - TITLE STATEMENT | |
| Title | An Introduction to Duplicate Detection |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2010. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | IX, 77 p. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Synthesis Lectures on Data Management, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Data Cleansing: Introduction and Motivation -- Problem Definition -- Similarity Functions -- Duplicate Detection Algorithms -- Evaluating Detection Success -- Conclusion and Outlook -- Bibliography. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | With the ever increasing volume of data, data quality problems abound. Multiple, yet different representations of the same real-world objects in data, duplicates, are one of the most intriguing data quality problems. The effects of such duplicates are detrimental; for instance, bank customers can obtain duplicate identities, inventory levels are monitored incorrectly, catalogs are mailed multiple times to the same household, etc. Automatically detecting duplicates is difficult: First, duplicate representations are usually not identical but slightly differ in their values. Second, in principle all pairs of records should be compared, which is infeasible for large volumes of data. This lecture examines closely the two main components to overcome these difficulties: (i) Similarity measures are used to automatically identify duplicates when comparing two records. Well-chosen similarity measures improve the effectiveness of duplicate detection. (ii) Algorithms are developed to perform on very large volumes of data in search for duplicates. Well-designed algorithms improve the efficiency of duplicate detection. Finally, we discuss methods to evaluate the success of duplicate detection. Table of Contents: Data Cleansing: Introduction and Motivation / Problem Definition / Similarity Functions / Duplicate Detection Algorithms / Evaluating Detection Success / Conclusion and Outlook / Bibliography. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Herschel, Melanie. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-3-031-01835-0 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2010. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
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| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
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| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer networks . |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data structures (Computer science). |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Information theory. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Communication Networks. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data Structures and Information Theory. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 2153-5426 |
| 912 ## - | |
| -- | ZDB-2-SXSC |
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