Ontology Learning by Clustering Based on Fuzzy Formal Concept Analysis

Ontology is an important tool of knowledge representation, but its construction is a difficult and tedious task. Ontology constructed by formal concept analysis is quite complicated in terms of the number of concepts generated and can not deal with the vague and uncertain information in practice. A new method is developed to create fuzzy ontology by clustering on Fuzzy Formal Concept Analysis. In the end, experimental results on artificially generated datasets are produced which shows that the learning algorithm has excellent performance on the time-spatial complexity.