Graph-theoretic autofill
This addresses the issue of incomplete data entry in interactive web applications, such as salary estimators or medical diagnosis tools, by providing a more sophisticated alternative to fixed defaults.
The paper tackles the problem of handling missing input values in web forms at run-time by proposing two new graph-theoretic approaches that use predefined dependencies between fields to autofill missing values iteratively, with directed loopless graphs as the mathematical model.
Imagine a website that asks the user to fill in a web form and -- based on the input values -- derives a relevant figure, for instance an expected salary, a medical diagnosis or the market value of a house. How to deal with missing input values at run-time? Besides using fixed defaults, a more sophisticated approach is to use predefined dependencies (logical or correlational) between different fields to autofill missing values in an iterative way. Directed loopless graphs (in which cycles are allowed) are the ideal mathematical model to formalize these dependencies. We present two new graph-theoretic approaches to filling missing values at run-time.