Generating facets for phone-based navigation of structured data

Designing interactive voice systems that have optimum cognitive load on callers has been an active research topic for quite some time. There have been many studies comparing the user preferences on navigation trees with higher depths over higher breadths. In this paper, we consider the navigation of structured data containing various types of attributes using phone-based interactions. This problem is particularly relevant to emerging economies in which innovative voice-based applications are being built to address semi-literate population. We address the problem of identifying the right sequence of facets to be presented to the user for phone-based navigation of the data in two stages. Firstly, we perform extensive user studies in the target population to understand the relation between the nature of facets (attributes) of the data and the cognitive load. Secondly, we propose an algorithm to design optimum navigation trees based on the inferences made in the first phase. We compare the proposed algorithm with the traditional facet generation algorithms with respect to various factors and discuss the optimality of the proposed algorithm.