Course Recommendation System Based On Knowledge Entity

Compared to the industry technology innovation the update of the university's training curriculum is relatively sluggish.College students need to acquire more knowledge through extracurricular course and practice so that they can gain more advantages in the recruitment process.The current course recommendation is not attractive to college students.The mainspring of it all is the inaccurate self-positioning of college students and the insufficient course recommendation system for employment.This paper analyzes some recruitment information of IT directions by naming entity recognition technology,and recommends courses to college students.As one of the most popular data acquisition methods,crawler technology is also the main method of obtaining data in this paper.This article uses Scrapy framework to build a distributed crawler which can crawl some IT directions recruitment information from Zhilian,51 job and the course information from Imooc,Udacity.The information serves as data sources,and will be stored in Redis database.Named entity as an important carrier for texts carrying key information is the main directions of our research.Named entity recognition is one of the basic tasks of natural language processing which is widely used in text mining,information extraction,knowledge quiz,semantic analysis,machine translation and other fields.In the big data-driven production and life,how to extract valuable information efficiently becomes a top priority issue.In this paper,we use the current more popular named entity model BiLSTM-CRF to identify the knowledge entity.The knowledge entities extracted from the recruitment information,including programming capabilities,application frameworks,operating systems,algorithmic techniques,and related software.Extracting knowledge entities through named entity recognition technology plays an important role in job information analysis.Finally,based on the recruitment information,course information and knowledge entities,a course recommendation system was established.By searching based on search terms,the distribution of knowledge entities in relevant positions is analyzed,and on this basis,the course information that college students should obtain is analyzed.