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Visual representation of data like charts and tables can be challenging tounderstand for readers. Previous work showed that combining visualisations withtext can improve the communication of insights in static contexts, but littleis known about interactive ones. In this work we present an NLG chatbot thatprocesses natural language queries and provides insights through a combinationof charts and text. We apply it to nutrition, a domain communication quality iscritical. Through crowd-sourced evaluation we compare the informativeness ofour chatbot against traditional, static diet-apps. We find that theconversational context significantly improved users' understanding of dietarydata in various tasks, and that users considered the chatbot as more useful andquick to use than traditional apps.

Comparing informativeness of an NLG chatbot vs graphical app in diet-information domain