We develop a three-step fuzzy logic-based algorithm for clustering categorical attributes, and we apply it to analyze cultural data. In the first step the algorithm employs an entr...
George E. Tsekouras, Dimitris Papageorgiou, Sotiri...
- In this work we are analyzing scalability of the heuristic algorithm we used in the past [1-4] to discover knowledge from multi-valued symbolic attributes in fuzzy databases. The...
The grade of membership (GoM) model uses fuzzy sets as memberships of each individual to extreme profiles (or classes) on the likelihood function of multivariate multinomial distr...
— This paper introduces a quantitative method for social data analysis, which is based on the use of categorical data clustering. More specifically, we employ categorical data cl...
Partitioning a large set of objects into homogeneous clusters is a fundamental operation in data mining. The k-means algorithm is best suited for implementing this operation becau...