English Personalized Reading Mode Based on Data Mining Technology

Abstract

Data mining technology has received great attention in recent years. It can automatically select the appropriate data for analysis and retrieval in large complex and rich data, and can solve the challenges of high capacity, high speed and diversity brought by big data. Using data mining technology to extract rules, data mining and analysis can provide effective decision-making reference. At present, English reading learning is not only classroom textbook reading learning, but also students can gain English reading information through a large number of personalized reading, enrich their English knowledge and improve their reading appreciation level. Data mining technology can automatically analyze and mine according to the users' previous English reading habits, and recommend books service that can meet the users' personalized English reading habits. This paper mainly studies the English Personalized reading(EPR) mode based on data mining technology. This paper studies the data mining process of data mining technology, analyzes the characteristics of personalized reading, and understands the personalized reading function based on data mining technology. In order to understand the necessity of data mining technology to recommend Personalized English reading, this paper uses data mining technology to understand users' reading habits. After using data mining technology to recommend Personalized English reading mode, through the form of questionnaire survey to understand the user's attitude towards personalized English reading mode. The experimental results show that 83% of the users like the personalized English reading mode after using the personalized English reading mode based on data mining technology, 16% of the users are indifferent to its appearance, and only 1% of the users do not like the personalized English reading mode.