Improved Apriori Algorithm in Higher Vocational English Education Information Data Mining

With the development of science and technology, the amount of data related to education has been growing. Data mining and data analysis technologies have promoted the reform of education model and teaching evaluation system. In order to solve the shortcomings of existing English education information data mining research, this paper briefly introduces the process of data mining and English education information data mining in higher vocational colleges. This paper introduces the big data model designer of higher vocational English education information and the design configuration of higher vocational English education information basic platform. An improved Aprioiii algorithm based on matrix is proposed. Through Aprioiii algorithm, data mining is carried out for three subject information: curriculum association, curriculum and basic information association, and teaching mode association. It is specifically applied to mining association rules in teaching mode management. The mining results show that students are familiar with textbooks, prepare lessons carefully, and have rich content Large amount of information) - excellent ⇒ (skilled explanation, clear organization, easy to understand, and strong logic. Its support and confidence are 34.5% and 86.2% respectively. Therefore, the feasibility of the improved Apriori algorithm in information data mining of higher vocational English education is verified.