Decision making using data is dependent on the quality of the data being used to make those decisions. Currently, data-to-text recommendation systems do not take this into consideration. Unsatisfactory recommendations are likely to cause further damage, which could have a detrimental effect economically or from a health and safety perspective. Highlighting quality issues in data-to-text systems will allow readers to consider this.
|Journal||CEUR Workshop Proceedings|
|Early online date||1 Jan 2018|
|Publication status||Published - 1 Jan 2018|
|Event||1st SICSA Workshop on Reasoning, Learning and Explainability, ReaLX 2018 - Aberdeen, United Kingdom|
Duration: 27 Jun 2018 → 27 Jun 2018
- Data quality