Requirement driven structuring for data marketplace by conversational AI model

Proposal of a New Data Market Structure through Conversational AI

Abstract

In former data markets, there is a lack of diversity and quantity of data. Even if there was a plenty of data sets, it was often difficult to obtain the desired data. Instead of relying on data experts to supply data, this paper propose a methodology that can be applied to data collection and data transactions by specifying ambiguous requirements through conversational AI model. The goal of this methodology is to increase the amount and diversity of data in the data market and to spread data-based labor through innovation in data collection and transaction. The method proposed here helps to structure issues by breaking them down into data variables, which makes it easier to collect diverse data. Therefore, data providers are able to offer a wider range of data within the marketplace.