Provided are an adaptive knowledge base construction system and method. The adaptive knowledge base construction system includes a machine learning engine analyzing a correlation between pieces of data included in a first data set in a process of learning the first data set input thereto, based on machine learning, a rule generator generating a rule based on the machine learning by using an analysis result obtained by analyzing the correlation, and a semantic rule generator generating a semantic rule from the rule based on the machine learning by using a language expressing ontology, and reflecting the generated semantic rule in a knowledge base to extend the knowledge base.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. An adaptive knowledge base construction system comprising: a machine learning engine analyzing a correlation between pieces of data included in a first data set in a process of learning the first data set input thereto, based on machine learning; a rule generator generating a rule based on the machine learning by using an analysis result obtained by analyzing the correlation; and a semantic rule generator generating a semantic rule from the rule based on the machine learning by using a language expressing ontology, and reflecting the generated semantic rule in a knowledge base to extend the knowledge base. 2. The adaptive knowledge base construction system of claim 1, wherein the rule generator generates the rule by using one of a tree-based rule generation algorithm and an Apriori algorithm. 3. The adaptive knowledge base construction system of claim 1, further comprising: a rule modeler providing the semantic rule generator with a rule model for changing a method of generating the semantic rule. 4. The adaptive knowledge base construction system of claim 3, wherein the semantic rule generator performs semantic filtering on the rule by using the rule model provided from the rule modeler. 5. An adaptive knowledge base construction system comprising: a memory storing a program for providing an adaptive knowledge base construction model; and a processor executing the program, wherein by executing the program, the processor generates a learning model corresponding to a first data set input thereto, outputs a correlation analysis result obtained by analyzing the first data set according to the generated learning model, generates a machine learning rule based on a correlation analysis result obtained by analyzing a correlation between a learned model and a learned algorithm, and generates a semantic rule by using the generated machine learning rule. 6. The adaptive knowledge base construction system of claim 5, wherein the processor converts the machine learning rule into a semantic rule by using a language expressing one ontology of resource description framework (RDF) and ontology Web language (OWL). 7. The adaptive knowledge base construction system of claim 5, wherein the processor generates a learning model and an inference model corresponding to the first data set and a newly input second data set. 8. The adaptive knowledge base construction system of claim 5, wherein the processor generates a semantic rule by using a rule model input by a domain expert. 9. An adaptive knowledge base construction method comprising: performing machine learning on an input first data set; generating a machine learning-based rule, based on a learned result; converting the machine learning-based rule into a semantic rule by using a language expressing ontology; and storing the semantic rule to construct a knowledge base. 10. The adaptive knowledge base construction method of claim 9, wherein the language expressing the ontology is one of resource description framework (RDF) and ontology Web language (OWL). 11. The adaptive knowledge base construction method of claim 9, wherein the generating of the rule comprises generating the rule by using one of a tree-based rule generation algorithm and an Apriori algorithm.