An Episode-based Fuzzy Inference Mechanism for Chinese News Ontology Construction

摘要

Ontology is increasingly important in knowledge management and Semantic Web. The problem of it is that the construction of ontology is a time-consuming job and ontology engineers need to spend much time to maintain it. In this paper, we propose an episode-based fuzzy inference mechanism to extract domain ontology from unstructured Chinese news documents. In addition, the Self-Organization Map (SOM) algorithm is also adopted for concept clustering and taxonomic relation defined. Moreover, the attributes and operations of concepts can be extracted based on episodes for object-oriented ontology construction. Meanwhile, the non-taxonomic relations will be generated based on episodes. The three-layer parallel fuzzy inference mechanism will further be applied to obtain new instances for ontology learning. The experimental results show that our approach can effectively construct the Chinese news domain ontology.