A Comparative Study on Questionnaire Design for Categorization Based on Fuzzy Co-clustering Concept and Multi-view Possibilistic Partition - Yang, Ruixin; Honda, Katsuhiro; Ubukata, Seiki; Notsu, Akira (International Conference on Fuzzy Theory and Its Applications (Print), 2019)
This paper considers the problem of designing a questionnaire for categorization of subjects. In order to well-organize the categorical structures of subjects, co-cluster information is utilized based on two different co-clustering approaches under multi-view situations. A comparative experiment studies the characteristics of fuzzy co-clustering-based categorization, where all categories are simultaneously extracted in a batch process, and possibilistic partition-based categorization, where each co-cluster is independently extracted under each view of categories.