Thematic Fuzzy Clusters with an Additive Spectral Approach

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


This paper introduces an additive fuzzy clustering model for similarity data as oriented towards representation and visualization of activities of research organizations in a hierarchical taxonomy of the field. We propose a one-by-one cluster extracting strategy which leads to a version of spectral clustering approach for similarity data. The derived fuzzy clustering method, FADDIS, is experimentally verified both on the research activity data and in comparison with two state-of-the-art fuzzy clustering methods. Two developed simulated data generators, affinity data of Gaussian clusters and genuine additive similarity data, are described, and comparison of the results over this data are reported.
Original languageUnknown
Title of host publicationLecture Notes in Artifitial Intelligence (LNAI)
Publication statusPublished - 1 Jan 2011
EventPortuguese Conference on Artificial Intelligence (EPIA 2011) -
Duration: 1 Jan 2011 → …


ConferencePortuguese Conference on Artificial Intelligence (EPIA 2011)
Period1/01/11 → …

Cite this