We are happy to announce that our vision paper "A Scoring-based Approach for Data Preparator Suggestion" has been accepted at LWDA 2019.
Authors: Lan Jiang, Gerardo Vitagliano, and Felix Naumann
Abstract: Self-service data preparation enables end users to prepare data by themselves. However, the plethora of possible data preparation steps can overwhelm the user. We introduce a score-based preparator ranking approach to propose preparator candidates in a context-specific manner. To this end, we give scoring functions for a selected set of preparators and outline future work towards a full-fledged data preparation system.