Rule-based spreadsheet data transformation from arbitrary to relational tables
作者：
Highlights：
• Spreadsheet data transformation can be considered as table understanding.
• The two-layered table object model represents arbitrary spreadsheet tables.
• Our rule-based language enables to express consecutive steps of table understanding.
• Execution of the rules provides recovering implicit table semantic (structure).
• A rule-set allows converting arbitrary tables of the same genre into databases.
摘要
•Spreadsheet data transformation can be considered as table understanding.•The two-layered table object model represents arbitrary spreadsheet tables.•Our rule-based language enables to express consecutive steps of table understanding.•Execution of the rules provides recovering implicit table semantic (structure).•A rule-set allows converting arbitrary tables of the same genre into databases.
论文关键词：Spreadsheet data transformation,Table understanding,Table model,Table analysis,Table interpretation,Rule-based programming
论文评审过程：Received 28 June 2017, Revised 11 August 2017, Accepted 12 August 2017, Available online 14 August 2017, Version of Record 17 August 2017.
论文官网地址：https://doi.org/10.1016/j.is.2017.08.004
