Automatic Generation of Conversational Interfaces for Tabular Data Analysis
This addresses the challenge for non-technical users in exploiting open tabular data, though it is incremental as it builds on existing chatbot and data analysis methods.
The authors tackled the problem of limited access to tabular data by proposing automatically generated chatbots that provide conversational interfaces for data exploration and analytics, enabling non-technical users to interact with data through charts.
Tabular data is the most common format to publish and exchange structured data online. A clear example is the growing number of open data portals published by public administrations. However, exploitation of these data sources is currently limited to technical people able to programmatically manipulate and digest such data. As an alternative, we propose the use of chatbots to offer a conversational interface to facilitate the exploration of tabular data sources, including support for data analytics questions that are responded via charts rendered by the chatbot. Moreover, our chatbots are automatically generated from the data source itself thanks to the instantiation of a configurable collection of conversation patterns matched to the chatbot intents and entities.