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Sampling dirty data for matching attributes

Authors:

Henning Köhler,

Kerry TaylorAuthors Info & Claims

SIGMOD '10: Proceedings of the 2010 ACM SIGMOD International Conference on Management of data

Pages 63 - 74

https://doi.org/10.1145/1807167.1807177

Published: 06 June 2010 Publication History

Abstract

We investigate the problem of creating and analyzing samples of relational databases to find relationships between string-valued attributes. Our focus is on identifying attribute pairs whose value sets overlap, a pre-condition for typical joins over such attributes. However, real-world data sets are often 'dirty', especially when integrating data from different sources. To deal with this issue, we propose new similarity measures between sets of strings, which not only consider set based similarity, but also similarity between strings instances. To make the measures effective, we develop efficient algorithms for distributed sample creation and similarity computation. Test results show that for dirty data our measures are more accurate for measuring value overlap than existing sample-based methods, but we also observe that there is a clear tradeoff between accuracy and speed. This motivates a two-stage filtering approach, with both measures operating on the same samples.

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Cited By

Koehler HLink S(2024)Entity/Relationship Profiling2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00411(5393-5396)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00411
Wu FSong HYin JGao LBaldi MAnand N(2021)NEMA: Automatic Integration of Large Network Management DatabasesIEEE Transactions on Network and Service Management10.1109/TNSM.2020.303641418:3(3783-3797)Online publication date: Sep-2021
https://doi.org/10.1109/TNSM.2020.3036414
Ding GSun SWang G(2020)Schema matching based on SQL statementsDistributed and Parallel Databases10.1007/s10619-019-07268-938:1(193-226)Online publication date: 1-Mar-2020
https://dl.acm.org/doi/10.1007/s10619-019-07268-9
Show More Cited By

Index Terms

Sampling dirty data for matching attributes
1. Information systems
  1. Data management systems
    1. Database design and models

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Published In

cover image ACM Conferences

SIGMOD '10: Proceedings of the 2010 ACM SIGMOD International Conference on Management of data

June 2010

1286 pages

ISBN:9781450300322

DOI:10.1145/1807167

General Chair:
Ahmed Elmagarmid
Purdue University, USA
,
Program Chair:
Divyakant Agrawal
University of California at Santa Barbara, USA

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 06 June 2010

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SIGMOD/PODS '10

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SIGMOD/PODS '10: International Conference on Management of Data

June 6 - 10, 2010

Indiana, Indianapolis, USA

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Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

Koehler HLink S(2024)Entity/Relationship Profiling2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00411(5393-5396)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00411
Wu FSong HYin JGao LBaldi MAnand N(2021)NEMA: Automatic Integration of Large Network Management DatabasesIEEE Transactions on Network and Service Management10.1109/TNSM.2020.303641418:3(3783-3797)Online publication date: Sep-2021
https://doi.org/10.1109/TNSM.2020.3036414
Ding GSun SWang G(2020)Schema matching based on SQL statementsDistributed and Parallel Databases10.1007/s10619-019-07268-938:1(193-226)Online publication date: 1-Mar-2020
https://dl.acm.org/doi/10.1007/s10619-019-07268-9
He PHe JYao HLi PJi Y(2019)Application of Data Distribution Technology in Smart CitiesProcedia Computer Science10.1016/j.procs.2019.11.291162:C(324-330)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1016/j.procs.2019.11.291
Zhang JTay Y(2016)DscalerProceedings of the VLDB Endowment10.14778/3007328.30073339:14(1671-1682)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.14778/3007328.3007333
Ding GSun T(2015)Schema matching based on position of attribute in query statementKnowledge-Based Systems10.1016/j.knosys.2014.11.00575:C(41-51)Online publication date: 1-Feb-2015
https://dl.acm.org/doi/10.1016/j.knosys.2014.11.005
Wang H(2014)Duplicate Record Detection for Data IntegrationInnovative Techniques and Applications of Entity Resolution10.4018/978-1-4666-5198-2.ch014(339-358)Online publication date: 2014
https://doi.org/10.4018/978-1-4666-5198-2.ch014
Chen DKonrad CYi KYu WZhang QDyreson CLi FÖzsu M(2014)Robust set reconciliationProceedings of the 2014 ACM SIGMOD International Conference on Management of Data10.1145/2588555.2610528(135-146)Online publication date: 18-Jun-2014
https://dl.acm.org/doi/10.1145/2588555.2610528
Munir SKhan FRiaz M(2014)An instance based schema matching between opaque database schemas2014 4th International Conference on Engineering Technology and Technopreneuship (ICE2T)10.1109/ICE2T.2014.7006242(177-182)Online publication date: Aug-2014
https://doi.org/10.1109/ICE2T.2014.7006242
Zhu JYang YXie QWang LHassan S(2014)Robust hybrid name disambiguation framework for large databasesScientometrics10.1007/s11192-013-1151-098:3(2255-2274)Online publication date: 1-Mar-2014
https://dl.acm.org/doi/10.1007/s11192-013-1151-0
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