Developing a Fuzzy Knowledge Base and Filling It with Knowledge Extracted from Various Documents

The article describes the process of developing a fuzzy knowledge base. The content of the fuzzy knowledge base is the result of extracting knowledge from the set of documents by subject area. Set of documents consists of the wiki-resources, UML-diagrams, documents and source code of projects. Knowledge base based on the graph database Neo4j. An attempt to implement the mechanism of inference by the contents of a graph database was made. This mechanism is used to generate the screen forms of the user interface dynamically. The contexts allow representing the content of the fuzzy knowledge base in space and time. Each space context is assigned a linguistic label, for example, low, middle, high. This label determines the competence of the expert in the given subject area. Time contexts allow storing the history of the knowledge base content changes. It allows returning to a specific state of the contents of the knowledge base.