Research of Conceptual Relation Extraction Based on Improved Hierarchical Clustering Method

ABSTRACT

The main task of Ontology learning is concept extraction and conceptual relation extraction. This paper mainly studies the latter. Conceptual relation consists of taxonomic relation and non-taxonomic relation. It introduces hierarchy clustering method, and uses concept hierarchy clustering method which chooses different clustering standards in each hierarchy to obtain the taxonomic relation. It improves the accuracy of the relationship extraction. For extracting the nontaxonomic relation, this paper uses a extended association rule, this method can get concrete names of relation, and confirms the domain and range. In the end, the paper uses the introduced method of Ontology Learning to constructing a domain ontology in the law. And it completes the implementation of an Ontology-based semantic retrieval system. The final effect of this system application demonstrates that this Ontology learning method is efficient.

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