A great number of companies and institutions use spreadsheets for managing, publishing and sharing their data. Though effective, spreadsheets are mainly designed for being interpreted by humans, and the automatic extraction of their content and interpretation is a complex task. The task becomes even harder when tables present different kinds of mistakes and their layout is complex. In this paper, we outline the approach that we wish to develop during the PhD for answering the research question “how to semi-automatically extract coherent semantic information from heterogeneous and complex spreadsheets?”.

Semantic Integration of Heterogeneous and Complex Spreadsheet Tables / S. Bonfitto. ((Intervento presentato al 25. convegno International Conference on Database Systems for Advanced Applications, DASFAA 2021 tenutosi a Taiwan nel 2021.

Semantic Integration of Heterogeneous and Complex Spreadsheet Tables

S. Bonfitto
Primo
2021

Abstract

A great number of companies and institutions use spreadsheets for managing, publishing and sharing their data. Though effective, spreadsheets are mainly designed for being interpreted by humans, and the automatic extraction of their content and interpretation is a complex task. The task becomes even harder when tables present different kinds of mistakes and their layout is complex. In this paper, we outline the approach that we wish to develop during the PhD for answering the research question “how to semi-automatically extract coherent semantic information from heterogeneous and complex spreadsheets?”.
13-apr-2021
Heterogeneous spreadsheet tables; Machine learning; Semantic table interpretation; User interfaces
Settore INF/01 - Informatica
Semantic Integration of Heterogeneous and Complex Spreadsheet Tables / S. Bonfitto. ((Intervento presentato al 25. convegno International Conference on Database Systems for Advanced Applications, DASFAA 2021 tenutosi a Taiwan nel 2021.
Conference Object
File in questo prodotto:
File Dimensione Formato  
paper_656.pdf

accesso aperto

Tipologia: Pre-print (manoscritto inviato all'editore)
Dimensione 296.6 kB
Formato Adobe PDF
296.6 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/880583
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact