Taxonomy Ontology Searching Method Based on Fuzzy Clustering
Zhao Yangyao, Shengchun Deng, Wang Nianbin · 2009
Following with the rapid development of e-commerce Websites and on-line business, how to aggregate and unify information from millions of on-line ontologies becomes an important searching field. In order to solve this problem among taxonomy ontologies, this paper proposed a searching method based on fuzzy clustering. The similarity among different conceptions can be well calculated by fuzzy clustering. Getting the queries from users, this method can both give the final searching answers according to the similarity and arrange these answers in special order which can be defined by users or system designers. During the discussion, an instance which used this method in sports clothes selling Websites was given out. What is more, a propositional answer method which can reveal the relationship among the answers was described. In conclusion, fuzzy clustering method can work well in analyzing concept similarity among e-commerce Websites.