Data Filling Approach of Soft Sets under Incomplete Information

Incomplete information in a soft set restricts the usage of the soft set. To make the incomplete soft set more useful, in this paper, we propose a data filling approach for incomplete soft set in which missing data is filled in terms of the association degree between the parameters when stronger association exists between the parameters or in terms of the probability of objects appearing in the mapping sets of parameters when no stronger association exists between the parameters. An illustrative example is employed to show the feasibility and validity of our approach in practical applications.