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Online data fusion

Authors:

Divesh SrivastavaAuthors Info & Claims

Proceedings of the VLDB Endowment, Volume 4, Issue 11

Pages 932 - 943

https://doi.org/10.14778/3402707.3402731

Published: 01 August 2011 Publication History

Abstract

The Web contains a significant volume of structured data in various domains, but a lot of data are dirty and erroneous, and they can be propagated through copying. While data integration techniques allow querying structured data on the Web, they take the union of the answers retrieved from different sources and can thus return conflicting information. Data fusion techniques, on the other hand, aim to find the true values, but are designed for offline data aggregation and can take a long time.

This paper proposes Solaris, the first online data fusion system. It starts with returning answers from the first probed source, and refreshes the answers as it probes more sources and applies fusion techniques on the retrieved data. For each returned answer, it shows the likelihood that the answer is correct, and stops retrieving data for it after gaining enough confidence that data from the unprocessed sources are unlikely to change the answer. We address key problems in building such a system and show empirically that the system can start returning correct answers quickly and terminate fast without sacrificing the quality of the answers.

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Cited By

Wang HChaoYin Bai YGuo DYue XChen JYu C(2024)Multi-Agent-based Multi-source Information Fusion Processing Method for Pressure Equipment Operation and Maintenance2024 IEEE 4th International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA)10.1109/ICIBA62489.2024.10869018(107-111)Online publication date: 6-Dec-2024
https://doi.org/10.1109/ICIBA62489.2024.10869018
Fang XWang XSheng QYao L(2024)Generalizing truth discovery by incorporating multi-truth featuresComputing10.1007/s00607-024-01288-9106:5(1557-1583)Online publication date: 22-Apr-2024
https://dl.acm.org/doi/10.1007/s00607-024-01288-9
Jaradat ASafieddine FDeraman AAli OAl-Ahmad AAlzoubi Y(2022)A Probabilistic Data Fusion Modeling Approach for Extracting True Values from Uncertain and Conflicting AttributesBig Data and Cognitive Computing10.3390/bdcc60401146:4(114)Online publication date: 13-Oct-2022
https://doi.org/10.3390/bdcc6040114
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Online data fusion
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Information & Contributors

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Published In

cover image Proceedings of the VLDB Endowment

Proceedings of the VLDB Endowment Volume 4, Issue 11

August 2011

520 pages

ISSN:2150-8097

Editor:
H. V. Jagadish

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VLDB Endowment

Publication History

Published: 01 August 2011

Published in PVLDB Volume 4, Issue 11

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Cited By

Wang HChaoYin Bai YGuo DYue XChen JYu C(2024)Multi-Agent-based Multi-source Information Fusion Processing Method for Pressure Equipment Operation and Maintenance2024 IEEE 4th International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA)10.1109/ICIBA62489.2024.10869018(107-111)Online publication date: 6-Dec-2024
Fang XWang XSheng QYao L(2024)Generalizing truth discovery by incorporating multi-truth featuresComputing10.1007/s00607-024-01288-9106:5(1557-1583)Online publication date: 22-Apr-2024
Jaradat ASafieddine FDeraman AAli OAl-Ahmad AAlzoubi Y(2022)A Probabilistic Data Fusion Modeling Approach for Extracting True Values from Uncertain and Conflicting AttributesBig Data and Cognitive Computing10.3390/bdcc60401146:4(114)Online publication date: 13-Oct-2022
Azzalini FPiantella DRabosio ETanca L(2022)Enhancing domain-aware multi-truth data fusion using copy-based source authority and value similarityThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-022-00757-x32:3(475-500)Online publication date: 19-Jul-2022
Ye CWang HDai GYe CWang HDai G(2022)IntroductionKnowledge Discovery from Multi-Sourced Data10.1007/978-981-19-1879-7_1(1-11)Online publication date: 14-Jun-2022
Dong XSrivastava D(2022)Big Data IntegrationundefinedOnline publication date: 23-Feb-2022
Becerra MTobón CCastro-Ospina APeluffo-Ordóñez D(2021)Information Quality Assessment for Data Fusion SystemsData10.3390/data60600606:6(60)Online publication date: 8-Jun-2021
Kayes AKalaria RSarker IIslam MWatters PNg AHammoudeh MBadsha SKumara I(2020)A Survey of Context-Aware Access Control Mechanisms for Cloud and Fog Networks: Taxonomy and Open Research IssuesSensors10.3390/s2009246420:9(2464)Online publication date: 27-Apr-2020
Fang XSheng QWang XZhang WNgu AYang J(2020)From Appearance to EssenceACM Transactions on Intelligent Systems and Technology10.1145/341174911:6(1-24)Online publication date: 11-Sep-2020
Yousfi AEl Yazidi MZellou A(2020)HASSO: A Highly-Automated Source Selection and Ordering System Based on Data Quality Factors2020 International Conference on Advanced Computer Science and Information Systems (ICACSIS)10.1109/ICACSIS51025.2020.9263243(155-164)Online publication date: 17-Oct-2020
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