Optimization Technology of Text Classification in Hospital Library Database Based on Collaborative Filtering
Traditional hospital library database text classification depends on specified size,which cannot be implemented based on the browsing content of specific users.Therefore,a text classification optimization method for hospital library database based on collaborative filtering is proposed.The characteristics of users browsing the database text are regarded as items,and a semi-automatic coder collaborative filtering model is constructed to optimize the user item scoring matrix.The average score correction factor and popular item punishment factor are used to improve the similarity calculation.Introducing attention mech-anism to construct a CNN-SVM classification model,which takes user text browsing features as input to achieve text classifica-tion.Tests have shown that this method has the lowest RMSE for constructing a rating matrix,the lowest MAE value for rec-ommended library text reading features,and an F1 value of 96.5%in text classification,demonstrating good text classification performance.