Even though requirement gathering is an important step in the construction of any project, it imposes tedious work on the side of the system administrator. Recently, with the advent of data mining methods, many opportunities for improvements on the requirement gathering process have become available, one of the which is the use of recommender systems. Recommendation systems for requirements engineering can be used to provide the right information at the right time to requirements engineers. In this work, we propose a novel efficient recommender system based on Apriori algorithm for user requirements. Such recommender system would improve the accuracy of the obtained requirements and produce more comprehensive results. Furthermore, it would provide interesting information that can be used by various parties. Experimental work showed that our recommender system is efficient in term of execution time and can be widely implemented. In details, the system needed 11-21 seconds to execute when the number of users was 2000-4000.