Data and information quality assessment in a possibilistic framework based on the Choquet Integral

Abstract

Designing methods for assessment of data and information quality is a relatively new and rather difficult problem. This paper presents a new approach for data and information quality assessment in the possibilistic framework based on Choquet Integral. The aim is not only to estimate data or information quality but also to differentiate between two quality degrees that are very close. The methodology of the Choquet integral is extended to the possibilistic framework. The proposed approach is validated using both: synthetic data and benchmark datasets. The experimental results clearly show that the proposed approach is able to assess the quality of the considered data and information.