Cell Classification for Layout Recognition in Spreadsheets

  • Elvis KociEmail author
  • Maik Thiele
  • Oscar Romero
  • Wolfgang Lehner
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 914)


Spreadsheets compose a notably large and valuable dataset of documents within the enterprise settings and on the Web. Although spreadsheets are intuitive to use and equipped with powerful functionalities, extracting and reusing data from them remains a cumbersome and mostly manual task. Their greatest strength, the large degree of freedom they provide to the user, is at the same time also their greatest weakness, since data can be arbitrarily structured. Therefore, in this paper we propose a supervised learning approach for layout recognition in spreadsheets. We work on the cell level, aiming at predicting their correct layout role, out of five predefined alternatives. For this task we have considered a large number of features not covered before by related work. Moreover, we gather a considerably large dataset of annotated cells, from spreadsheets exhibiting variability in format and content. Our experiments, with five different classification algorithms, show that we can predict cell layout roles with high accuracy. Subsequently, in this paper we focus on revising the classification results, with the aim of repairing misclassifications. We propose a sophisticated approach, composed of three steps, which effectively corrects a reasonable number of inaccurate predictions.


Speadsheet Tabular Table Document Layout Recognition Analysis Classification 



This research has been funded by the European Commission through the Erasmus Mundus Joint Doctorate “Information Technologies for Business Intelligence - Doctoral College” (IT4BI-DC).


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Elvis Koci
    • 1
    • 2
    Email author
  • Maik Thiele
    • 1
  • Oscar Romero
    • 2
  • Wolfgang Lehner
    • 1
  1. 1.Database Technology Group, Department of Computer ScienceTechnische Universität DresdenDresdenGermany
  2. 2.Departament d’Enginyeria de Serveis i Sistemes d’InformaciòUniversitat Politecnica de CatalunyaBarcelonaSpain

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