The interaction between schema matching and record matching in data integration (extended abstract)

Binbin Gu; Zhixu Li; Xiangliang Zhang; An Liu; Guanfeng Liu; Kai Zheng; Lei Zhao; Xiaofang Zhou

doi:10.1109/ICDE.2017.23

The interaction between schema matching and record matching in data integration (extended abstract)

Binbin Gu, Zhixu Li, Xiangliang Zhang, An Liu, Guanfeng Liu, Kai Zheng, Lei Zhao, Xiaofang Zhou

King Abdullah University of Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Schema Matching (SM) and Record Matching (RM) are two necessary steps in integrating multiple relational tables of different schemas, where SM unifies the schemas and RM detects records referring to the same real-world entity. The two processes have been thoroughly studied separately, but few attention has been paid to the interaction of SM and RM. In this work we find that, even alternating them in a simple manner, SM and RM can benefit from each other to reach a better integration performance (i.e., in terms of precision and recall). Therefore, combining SM and RM is a promising solution for improving data integration.

Original language	English (US)
Title of host publication	2017 IEEE 33rd International Conference on Data Engineering (ICDE)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	33-34
Number of pages	2
ISBN (Print)	9781509065431
DOIs	https://doi.org/10.1109/ICDE.2017.23
State	Published - May 18 2017

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This research is partially supported by Natural Science Foundation of China (Grant No. 61402313, 61303019, 61472263, 61572336), the King Abdullah University of Science and Technology, the Australian Research Council (Grants No. DP120102829), the Postdoctoral scientific research funding of Jiangsu Province (No. 1501090B) and the National Postdoctoral Funding (No. 2015M581859, 2016T90493).

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10.1109/ICDE.2017.23

https://repository.kaust.edu.sa/bitstream/10754/624029/1/IntSRM-icdeShort.pdf

Cite this

@inproceedings{909b64381d414818869d4e1a9cd4b73e,

title = "The interaction between schema matching and record matching in data integration (extended abstract)",

abstract = "Schema Matching (SM) and Record Matching (RM) are two necessary steps in integrating multiple relational tables of different schemas, where SM unifies the schemas and RM detects records referring to the same real-world entity. The two processes have been thoroughly studied separately, but few attention has been paid to the interaction of SM and RM. In this work we find that, even alternating them in a simple manner, SM and RM can benefit from each other to reach a better integration performance (i.e., in terms of precision and recall). Therefore, combining SM and RM is a promising solution for improving data integration.",

author = "Binbin Gu and Zhixu Li and Xiangliang Zhang and An Liu and Guanfeng Liu and Kai Zheng and Lei Zhao and Xiaofang Zhou",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: This research is partially supported by Natural Science Foundation of China (Grant No. 61402313, 61303019, 61472263, 61572336), the King Abdullah University of Science and Technology, the Australian Research Council (Grants No. DP120102829), the Postdoctoral scientific research funding of Jiangsu Province (No. 1501090B) and the National Postdoctoral Funding (No. 2015M581859, 2016T90493).",

year = "2017",

month = may,

day = "18",

doi = "10.1109/ICDE.2017.23",

language = "English (US)",

isbn = "9781509065431",

pages = "33--34",

booktitle = "2017 IEEE 33rd International Conference on Data Engineering (ICDE)",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

}

The interaction between schema matching and record matching in data integration (extended abstract). / Gu, Binbin; Li, Zhixu; Zhang, Xiangliang et al.
2017 IEEE 33rd International Conference on Data Engineering (ICDE). Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 33-34.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - The interaction between schema matching and record matching in data integration (extended abstract)

AU - Gu, Binbin

AU - Li, Zhixu

AU - Zhang, Xiangliang

AU - Liu, An

AU - Liu, Guanfeng

AU - Zheng, Kai

AU - Zhao, Lei

AU - Zhou, Xiaofang

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: This research is partially supported by Natural Science Foundation of China (Grant No. 61402313, 61303019, 61472263, 61572336), the King Abdullah University of Science and Technology, the Australian Research Council (Grants No. DP120102829), the Postdoctoral scientific research funding of Jiangsu Province (No. 1501090B) and the National Postdoctoral Funding (No. 2015M581859, 2016T90493).

PY - 2017/5/18

Y1 - 2017/5/18

N2 - Schema Matching (SM) and Record Matching (RM) are two necessary steps in integrating multiple relational tables of different schemas, where SM unifies the schemas and RM detects records referring to the same real-world entity. The two processes have been thoroughly studied separately, but few attention has been paid to the interaction of SM and RM. In this work we find that, even alternating them in a simple manner, SM and RM can benefit from each other to reach a better integration performance (i.e., in terms of precision and recall). Therefore, combining SM and RM is a promising solution for improving data integration.

AB - Schema Matching (SM) and Record Matching (RM) are two necessary steps in integrating multiple relational tables of different schemas, where SM unifies the schemas and RM detects records referring to the same real-world entity. The two processes have been thoroughly studied separately, but few attention has been paid to the interaction of SM and RM. In this work we find that, even alternating them in a simple manner, SM and RM can benefit from each other to reach a better integration performance (i.e., in terms of precision and recall). Therefore, combining SM and RM is a promising solution for improving data integration.

UR - http://hdl.handle.net/10754/624029

UR - http://ieeexplore.ieee.org/document/7929919/

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DO - 10.1109/ICDE.2017.23

M3 - Conference contribution

SN - 9781509065431

SP - 33

EP - 34

BT - 2017 IEEE 33rd International Conference on Data Engineering (ICDE)

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -

The interaction between schema matching and record matching in data integration (extended abstract)

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