Abstract
Traditional database systems are passive because of its inability to react to events automatically. Active databases support event handling by monitoring and reacting to specific circumstances of relevance to an application. An event, a condition and an action are the three parts of the rules defined in active database systems.Relation databases can handle crisp data. However, the information in the real world is imprecise and vague. Fuzzy logic is used to handle uncertain data, which computes the degree to which something is true.
This project is designed to implement a system that incorporates fuzzy concepts and active rules into a graph database system. Specifically, rules triggered by mutation events are handled by this project. A user can specify fuzzy terms in the condition and action parts of a rule. This report describes a language model, architecture design, and an execution model in detail. A language model defines the rule structure and contains the metadata for rule processing. Architecture design identifies the system's architectural components and user interfaces including rule specification interface and query interface. The execution model handles rule processing and execution at run time. A supply chain application is used to demonstrate the examples of rule specification and execution.