گروه ریاضی و علوم رایانه؛ دانشگاه علامه طباطبایی
عنوان مقاله [English]
Today, due to massive amount of information, NoSQL databases are used to compute complex data. These databases are used to store semi-structured and unstructured data for big data management. In this paper, fuzzy queries are executed by users on the information stored in the Neo4j graph database, which show results in defuzzy manner. To evaluate the efficiency of the proposed method, we considered a database of manufacturing company. Price and quality fuzzy variables were considered and used to define and execute the fuzzy queries. The results can verify the performance of the proposed method. Additionally, a counselor (who has information about the data) defines fuzzy terms, membership functions, and fuzzy rules table. The most important process in this method is to find the center of gravity in order to defuzzify the final result. So, an algorithm has been implemented for this purpose by C # programming language. The greatest query time is due to find center of gravity. The evaluation results show that the increase in query time by using the proposed approach in comparison to query time by using Cypher language is acceptable due to the complexity of fuzzy concepts. Therefore, the proposed solution will be suitable for using ambiguous and fuzzy queries in large databases.