Research And Application Of Approach Of Ontology Learning Based On The Law Field

In the information age, the traditional retrieval method based on key words matching cannot meet the demand for information retrival. Because Ontology has clear concept hierarchy and good capabilities for semantic representation. More and more researchers have imported the Ontology into information retrieval to realize the semantics information retrieval.This paper applies Ontology to retrival system, to match content from semantic, in this way we can highly improve the effciency and accuracy of retrival system. It gives discussion and study of Ontology Learning. Firsly, it introduces some basical theories about Ontology and Ontology Learning. Then it lists some kinds of methods of concept extration. In light of some defects when the statisical methods only can extract double-word concepts, it adds the rule to abstracting compound words, and gives the method to abstract concepts having synonyms and the relationship of "is-a". The result of the experiment shows the feasibility of this method.For the relationship extraction, this paper also gives detailed discourse. It 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 non-taxonomic relation, this paper uses a extended association rule, this method can get concrete names of relationship, and confirms the domain and range.This paper uses the methods of Ontology Learning introuced in the third and forth chapters to constructing a domain ontology in the law at last. And it completes the impletemention of an Ontology-based semantic retrieval system. The final effect of this system application demonstrates that this Ontology learning method is efficient.