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The SearchEngine: A holistic approach to matching

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  • Doherr, Thorsten

Abstract

The SearchEngine is an open source project providing an integrated framework for diverse matching activities, especially the linkage of large scale firm data by fuzzy criteria like company names and addresses. At its core, it utilizes an efficient candidate retrieval mechanism implementing a word respectively token driven heuristic. Every record in one table becomes a search term to retrieve similar candidate records in the base table according to a search strategy replacing blocking strategies of conventional matching efforts. Because similarity is inherently established by the candidate selection, it is only required to filter false positives by using the meta data export file derived from the matching heuristic to implement a machine learning approach. This paper discusses the general foundation of the heuristic and the algorithm while two detailed walkthroughs of company linkages show practical examples.

Suggested Citation

  • Doherr, Thorsten, 2023. "The SearchEngine: A holistic approach to matching," ZEW Discussion Papers 23-001, ZEW - Leibniz Centre for European Economic Research.
    • Handle: RePEc:zbw:zewdip:23001
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    References listed on IDEAS

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    1. Doherr, Thorsten, 2021. "Disambiguation by namesake risk assessment," ZEW Discussion Papers 21-021, ZEW - Leibniz Centre for European Economic Research.
    2. Doherr, Thorsten, 2017. "Inventor mobility index: A method to disambiguate inventor careers," ZEW Discussion Papers 17-018, ZEW - Leibniz Centre for European Economic Research.
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    Cited by:

    1. Gottschalk, Sandra & Hauer, Annegret & Ahrens, Jan-Philipp, 2023. "Die volkswirtschaftliche Bedeutung der Familienunternehmen: 6. Auflage und Schwerpunkt "Ausbildungsengagement"," Studien, Stiftung Familienunternehmen / Foundation for Family Businesses, number 281018, March.
    2. Arabzadeh, Hamzeh & Balleer, Almut & Gehrke, Britta & Taskin, Ahmet Ali, 2024. "Minimum wages, wage dispersion and financial constraints in firms," European Economic Review, Elsevier, vol. 163(C).
    3. Breithaupt, Patrick & Hottenrott, Hanna & Rammer, Christian & Römer, Konstantin, 2023. "Mapping employee mobility and employer networks using professional network data," ZEW Discussion Papers 23-041, ZEW - Leibniz Centre for European Economic Research.

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    More about this item

    Keywords

    data linkage; firm matching; entity resolution; machine learning;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

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