An Improved Apriori Algorithm And Its Application In Trainee Selection Of Informatics Olympiad

Data mining is the hot issue in research of artificial intelligence.In the field of data mining,association rules mining is an important research direction. In recent years association rules is widely used in marketing,scientific research,medical treatment,network intrusion detection,education and other fields.What’s more,it achieved some results.Informatics Olympiad is one of five Olympic subjects in the middle school.It is a good platform for students to learn and develop themselves.In fact Informatics Olympiad is elite education.Among the five Olympic subjects,information science is the only one which is not requested in the the university entrance exam.It is faced with many difficulties during the process of conducting.Better students selection can succeed in getting twice the result with half the effort.Using the data mining technology in the Informatics Olympiad makes a contribution to the development of putting the result to promote Informatics Olympiad.Based on Informatics Olympiad students oriented questionnaire data samples,in this paper,the improved Apriori algorithm was applied to trainee selection of Informatics Olympiad.In this paper, the main content includes:1.Discuss the knowledge of data mining technology and association rule technology, focusing on the detailed description of the basic idea,the implementation process,limitations and the improved method in the classical association rules algorithm(Apriori algorithm).2.It presents an improved Apriori algorithm(Tire-Apriori algorithm),introducing the basic thought and theoretical basis of Tire-Apriori algorithm based on tree dictionary and transaction projection. The implementation step of Tire-Apriori algorithm are explained with examples.Tire-Apriori algorithm is realized by using c++ programming language. It is proved by experiments that the Tire-Apriori algorithm is more effective than the Apriori algorithm.3.Tire-Apriori algorithm was applied to trainee selection of Informatics Olympiad.Questionnaires are regarded as data source.This paper analyzed collection and pretreatment process of the data.Data is mined association rules in two different conditions by using Tire-Apriori algorithm.First, mining the relationship between winning and the characteristics of students explains offers the standard of the student selection for the coach. Second,mining the relationship between Informatics Olympiad and quality education attracts more capable students to Informatics Olympiad.