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A machine learning approach for layout inference in spreadsheets

Author
Koci, E.; Thiele, M.; Romero, O.; Lehner, W.
Type of activity
Presentation of work at congresses
Name of edition
8th International Joint Conference on Knowledge Discovery and Information Retrieval
Date of publication
2016
Presentation's date
2016-11
Book of congress proceedings
IC3K 2016: Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management: volume 1: KDIR
First page
77
Last page
88
Publisher
SciTePress
DOI
https://doi.org/10.5220/0006052200770088 Open in new window
Repository
http://hdl.handle.net/2117/100584 Open in new window
URL
http://dx.doi.org/10.5220/0006052200770088 Open in new window
Abstract
Spreadsheet applications are one of the most used tools for content generation and presentation in industry and the Web. In spite of this success, there does not exist a comprehensive approach to automatically extract and reuse the richness of data maintained in this format. The biggest obstacle is the lack of awareness about the structure of the data in spreadsheets, which otherwise could provide the means to automatically understand and extract knowledge from these files. In this paper, we pro...
Citation
Koci, E., Thiele, M., Romero, O., Lehner, W. A machine learning approach for layout inference in spreadsheets. A: International Conference on Knowledge Discovery and Information Retrieval. "IC3K 2016: Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management: volume 1: KDIR". Porto: SciTePress, 2016, p. 77-88.
Keywords
Knowledge discovery, Layout, Speadsheets, Structure, Tabular
Group of research
IMP - Information Modelling and Processing
inLab FIB

Participants

  • Koci, Elvis  (author and speaker )
  • Thiele, Maik  (author and speaker )
  • Romero Moral, Oscar  (author and speaker )
  • Lehner, Wolfgang  (author and speaker )

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