Research on ontology learning of Internet public sentiment concerning food safety
LI Hong-we · Journal of Nanjing University of Posts and Telecommunications · 2013
The ontology of Internet public sentiment concerning food safety can promote to some extend the extracting and searching efficiency of public sentiment information,but the ontology building on this issue needs to use the ontology learning technology due to its massive text information. The main tasks of ontology learning are concept extraction and concept relation extraction. In this research,the concept extraction method uses domain relevance and domain consensus,and the concept relation extraction method uses associative rules. Considering the composition of Chinese words,it further analyzes the concept relation based on judgment of distance between two words,which can be used for finding new concept and identifying some type of concept relation. In the end the domain ontology is learned from 229 domain documents of Lipton tea bags event.