TaCLe: Learning Constraints in Tabular Data
2017 (English)In: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, New York: Association for Computing Machinery , 2017, p. 2511-2514Conference paper, Published paper (Refereed)
Abstract [en]
Spreadsheet data is widely used today by many different people and across industries. However, writing, maintaining and identifying good formulae for spreadsheets can be time consuming and error-prone. To address this issue we have introduced the TaCLe system (Tabular Constraint Learner). The system tackles an inverse learning problem: given a plain comma separated file, it reconstructs the spreadsheet formulae that hold in the tables. Two important considerations are the number of cells and constraints to check, and how to deal with multiple formulae for the same cell. Our system reasons over entire rows and columns and has an intuitive user interface for interacting with the learned constraints and data. It can be seen as an intelligent assistance tool for discovering formulae from data. As a result, the user obtains a spreadsheet that can automatically recompute dependent cells when updating or adding data.
Place, publisher, year, edition, pages
New York: Association for Computing Machinery , 2017. p. 2511-2514
Keywords [en]
Relational Learning, Constraint Learning, Spreadsheets
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:oru:diva-91173DOI: 10.1145/3132847.3133193ISI: 000440845300330Scopus ID: 2-s2.0-85037350092ISBN: 978-1-4503-4918-5 (print)OAI: oai:DiVA.org:oru-91173DiVA, id: diva2:1545396
Conference
26th ACM International Conference on Information and Knowledge Management (CIKM 2017), Pan Pacific Singapore Hotel, Singapore, Singapore, November 6-10, 2017
Note
Funding Agencies:
FWO
ERC-ADG-201 project - European Research Council 694980 SYNTH
2021-04-192021-04-192021-04-19Bibliographically approved