Research on Recommendation of College Mental Health Teaching Materials Based on Improved Deep Learning Algorithm

Table 1

Analysis of shortcomings of recommended methods.

Method type	Shortcoming
Content-based recommendation	Sparse problem is serious, complex attributes are difficult to deal with, and more classifiers are needed
Collaborative filtering recommendation	Poor scalability, poor recommendation quality at the beginning of the system
Rule-based recommendation	Time consuming, low degree of personalization, and complex problems for new users
Utility-based recommendation	Poor flexibility and serious attribute overlap
Knowledge-based recommendation	Knowledge acquisition is difficult, and the recommendation method is static recommendation