TaCLe: Learning Constraints in Tabular Data

Sergey Paramonov, Samuel Kolb, Tias Guns, L. D. Raedt
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引用次数: 8

Abstract

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.
表格数据中的学习约束
电子表格数据今天被许多不同的人和跨行业广泛使用。然而,为电子表格编写、维护和识别好的公式既耗时又容易出错。为了解决这个问题,我们引入了TaCLe系统(表格约束学习器)。该系统解决了一个反向学习问题:给定一个逗号分隔的普通文件,它重建保存在表格中的电子表格公式。两个重要的考虑因素是单元格的数量和要检查的约束,以及如何处理同一单元格的多个公式。我们的系统对整个行和列进行推理,并具有直观的用户界面,用于与学习到的约束和数据进行交互。它可以看作是从数据中发现公式的智能辅助工具。因此,用户获得的电子表格可以在更新或添加数据时自动重新计算相关单元格。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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