| With the suggestion of the new generation Internet of the Semantic Web, there is an increasing concern of the semantic information.The purpose of Semantic Web research is to make the most of the online information with semantics which the computer can understand and handle. So the interaction between human and computer can be much easier. With the development of Semantic Web, it can promote the perfection of Semantic Web information retrieval technologies, so semantic retrieval of the relational Database systems has become an important research topic in the field of database retrieval.Query is a very important function of the Database. Common database query mainly uses string matching. However, with the improvement of system requirements, this simple query matching is no longer able to meet the demand. There are more and more information with semantic in the database. This information is very significant. Meanwhile, there are useful information with fuzzy semantic. People want to make use of and manage the useful information effectively so as to retrieve these data easily. The extension to the fuzzy semantic query of Database query seems particularly important.The key of the Database fuzzy semantic query is how to deal with the data with semantic information. First, this paper introduces fuzzy ontology and fuzzy linguistic variable ontology to define the concept of data with semantic information and introduces linguistic variable which is a new data type in Database to expand the capacity of the fuzzy semantic query as well. Second, this article extends SQLF by fuzzy linguistic variable ontology, so SQLF can deal with more complex fuzzy semantic query. Finally, this paper develops color ontology, gives the formal definition of ontology and the math model of fuzzy linguistic variable ontology and designs the fuzzy semantic retrieval system for the fashion database. |
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