Dealing with multi-valued data has become quite common in both the framework of databases as well as data analysis. Such data can be constrained by domain knowledge provided by relations between the variables and these relations are expressed by rules. However, such knowledge can introduce a...

This paper shows a fuzzy relational clustering method in order to perform the clustering of symbolic data. The presented method yields a fuzzy partition and prototype for each cluster by optimizing an adequacy criterion based on suitable dissimilarity measures. This work considers two...

The recording of symbolic data has become a common practice with the advances in database technologies. This paper shows hard and fuzzy relational clustering in order to partition symbolic data. These methods optimize objective functions based on a dissimilarity function. The distance used is a...

This study examines the limits of global corruption indicators based on experts’ perceptions. It draws on a wave of original surveys conducted in eight African countries that combined two types of approaches. The first approach covers a sample of over 35,000 people and uses experience-based...

The emergence of institutions, governance and especially corruption as major development considerations has generated a whole host of international databases intended to measure these concepts. These databases are now widely used in both the academic world and for public policies, especially for...