Abstract
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.
Original language | English |
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Journal | CEUR Workshop Proceedings |
Volume | 2151 |
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 |
Keywords
- Data quality
- Data-to-text
- Reasoning