Abstract
There is a lot of uncertain and imprecise information in the real-world scenario. Databases based on relational models support crisp and precise data. This project processed fuzzy quantified queries in the context of a graph database. Fuzzy logic allows decisions to be taken in a more realistic manner. This project designed a specific form of structural quantified query and demonstrated how it can be expressed as an extension to the Neo4j Cypher query language. This project implemented a system supporting temporal events using fuzzy active rules over Neo4j graph database systems. The project includes a language definition and an execution environment for fuzzy active timer rules for Neo4j Graph Databases. The language definition comprises of grammar which allows fuzzy expressions in the condition part of a rule. The rule engine was designed to facilitate the application of rules with various types of fuzzy distributions. The report includes a list of examples which demonstrated the usage of fuzzy expressions in queries. The project also evaluated the performance of the system by comparing the overhead of executing fuzzy queries with crisp queries.