Article

Matching Schemas in Online Communities: A Web 2.0 Approach

Authors:

Robert McCann,

Warren Shen,

AnHai DoanAuthors Info & Claims

ICDE '08: Proceedings of the 2008 IEEE 24th International Conference on Data Engineering

Pages 110 - 119

https://doi.org/10.1109/ICDE.2008.4497419

Published: 07 April 2008 Publication History

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Abstract

When integrating data from multiple sources, a key task that online communities often face is to match the schemas of the data sources. Today, such matching often incurs a huge workload that overwhelms the relatively small set of volunteer integrators. In such cases, community members may not even volunteer to be integrators, due to the high workload, and consequently no integration systems can be built. To address this problem, we propose to enlist the multitude of users in the community to help match the schemas, in a Web 2.0 fashion. We discuss the challenges of this approach and provide initial solutions. Finally, we describe an extensive set of experiments on both real-world and synthetic data that demonstrate the utility of the approach.

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Solomon MGenossar BGal AFekete JOmidvar-Tehrani BRong KShraga R(2024)CopycHats: Question Sequencing with Artificial AgentsProceedings of the 2024 Workshop on Human-In-the-Loop Data Analytics10.1145/3665939.3665963(1-7)Online publication date: 14-Jun-2024
https://dl.acm.org/doi/10.1145/3665939.3665963
Shraga R(2022)HumanALProceedings of the Workshop on Human-In-the-Loop Data Analytics10.1145/3546930.3547496(1-8)Online publication date: 12-Jun-2022
https://dl.acm.org/doi/10.1145/3546930.3547496
Shraga RGal A(2022)PoWareMatch: A Quality-aware Deep Learning Approach to Improve Human Schema MatchingJournal of Data and Information Quality10.1145/348342314:3(1-27)Online publication date: 23-May-2022
https://dl.acm.org/doi/10.1145/3483423
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Index Terms

Matching Schemas in Online Communities: A Web 2.0 Approach
1. Information systems
  1. Information retrieval

Index terms have been assigned to the content through auto-classification.

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ICDE '08: Proceedings of the 2008 IEEE 24th International Conference on Data Engineering

April 2008

1628 pages

ISBN:9781424418367

Publisher

IEEE Computer Society

United States

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Published: 07 April 2008

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Solomon MGenossar BGal AFekete JOmidvar-Tehrani BRong KShraga R(2024)CopycHats: Question Sequencing with Artificial AgentsProceedings of the 2024 Workshop on Human-In-the-Loop Data Analytics10.1145/3665939.3665963(1-7)Online publication date: 14-Jun-2024
https://dl.acm.org/doi/10.1145/3665939.3665963
Shraga R(2022)HumanALProceedings of the Workshop on Human-In-the-Loop Data Analytics10.1145/3546930.3547496(1-8)Online publication date: 12-Jun-2022
https://dl.acm.org/doi/10.1145/3546930.3547496
Shraga RGal A(2022)PoWareMatch: A Quality-aware Deep Learning Approach to Improve Human Schema MatchingJournal of Data and Information Quality10.1145/348342314:3(1-27)Online publication date: 23-May-2022
https://dl.acm.org/doi/10.1145/3483423
Doan AFranklin MKossmann DKraska T(2020)Crowdsourcing applications and platformsProceedings of the VLDB Endowment10.14778/3402755.34028094:12(1508-1509)Online publication date: 3-Jun-2020
https://dl.acm.org/doi/10.14778/3402755.3402809
Bernstein PMadhavan JRahm E(2020)Generic schema matching, ten years laterProceedings of the VLDB Endowment10.14778/3402707.34027104:11(695-701)Online publication date: 3-Jun-2020
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Crescenzi VFernandes AMerialdo PPaton N(2017)Crowdsourcing for data managementKnowledge and Information Systems10.1007/s10115-017-1057-x53:1(1-41)Online publication date: 1-Oct-2017
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El-Roby AAboulnaga ASellis TDavidson SIves Z(2015)ALEXProceedings of the 2015 ACM SIGMOD International Conference on Management of Data10.1145/2723372.2749428(1839-1853)Online publication date: 27-May-2015
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Matching large schemas: Approaches and evaluation

Building member attachment in online communities: applying theories of group identity and interpersonal bonds

What motivates members to contribute to enterprise online communities?

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