Research On Some Problems Of Dynamic Knowledge Bases

In the era of big data,analyzing and processing data has become a hot issue in the field of information technology,which is called data science.With the passage of time,the inflow or outflow of a large amount of data makes the database need to be updated at any time.This dissertation mainly studies the three problems of attribute reduction,knowledge structure and uncertainty measurement in dynamic knowledge base.First,we study the attribute reduction of the knowledge base in the dynamic environment under the homomorphism.There are a lot of complex database to deal with reality,but the huge database has brought us very inconvenient,so we need to compress the database to handle,homomorphism is a good mathematical tool of data compression in knowledge base,data compression is the direct method of attribute reduction and classification.Second,we discussed the changes in the knowledge structure of the dynamic knowledge base.Due to the change of dynamic knowledge base,the structure may also change.This may also have some influence on data compression.Therefore,it is necessary for us to study the knowledge structure of dynamic knowledge base.Third,we explored the uncertainty measurement of the dynamic knowledge base.In real life,continuous data inflows or outflows make us uncertain about the uncertainty of database.In order to understand the uncertainty of dynamic knowledge base,we measure the uncertainty of dynamic knowledge base.