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A Hybrid Machine-Crowdsourcing Approach for Web Table Matching and Cleaning

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Web-Age Information Management (WAIM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9659))

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Abstract

Table matching and data cleaning are two crucial activities in integrating data from different web tables, which have traditionally been considered as separate activities. We show that data cleaning can effectively help us discover table matches, and vice versa. In this paper, we study a hybrid machine-crowdsourcing approach to handle the two activities together with a well-developed knowledge base. Understanding the semantics of tables is fundamental to both matching and cleaning. We select the most valuable columns to crowdsourcing validation and infer others by consolidating crowdsourcing results and machine-generated results. When resolving inconsistency between data and semantics, relative trust is taken into account to validate data or semantics via crowd. Our experimental results show the effectiveness of the proposed approach for matching and cleaning web tables using real-life datasets.

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Acknowledgments

This work was partially supported by Chinese NSFC (61170020, 61402311, 61440053), Jiangsu Province Colleges and Universities Natural Science Research project (13KJB520021), Jiangsu Province Postgraduate Cultivation and Innovation project (CXZZ13_0813), and the US National Science Foundation (IIS-1115417).

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Authors and Affiliations

  1. School of Computer Science and Technology, Soochow University, Suzhou, China

    Chunhua Li, Pengpeng Zhao, Zhixu Li, Guanfeng Liu, Jian Wu & Zhiming Cui

  2. Department of Computer Science, University of Central Arkansas, Conway, USA

    Victor S. Sheng

Authors
  1. Chunhua Li
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  2. Pengpeng Zhao
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  3. Victor S. Sheng
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  4. Zhixu Li
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  5. Guanfeng Liu
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  6. Jian Wu
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  7. Zhiming Cui
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Corresponding author

Correspondence to Pengpeng Zhao .

Editor information

Editors and Affiliations

  1. Peking University , Beijing, China

    Bin Cui

  2. The George Washington University , Washington, D.C., USA

    Nan Zhang

  3. Hong Kong Baptist University, Kowloon Tong, Hong Kong, China

    Jianliang Xu

  4. University of Texas Rio Grande Valley, Edinburg, Texas, USA

    Xiang Lian

  5. Jiangxi University of Finance and Economics, Nanchang, Jiangxi, China

    Dexi Liu

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Li, C. et al. (2016). A Hybrid Machine-Crowdsourcing Approach for Web Table Matching and Cleaning. In: Cui, B., Zhang, N., Xu, J., Lian, X., Liu, D. (eds) Web-Age Information Management. WAIM 2016. Lecture Notes in Computer Science(), vol 9659. Springer, Cham. https://doi.org/10.1007/978-3-319-39958-4_11

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  • DOI: https://doi.org/10.1007/978-3-319-39958-4_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39957-7

  • Online ISBN: 978-3-319-39958-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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