id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_inn62q2rznhknhfgujiaek3ctm	Yang Ju	A Collaborative Filtering Recommendation Algorithm with Improved Similarity Calculation	2018	4	.pdf	application/pdf	2641	352	61	A Collaborative Filtering Recommendation Algorithm with Improved Similarity Improved Pearson collaborative filtering (IP-CF) algorithm is algorithm's similarity calculation, the prediction model is used Filtering; Similarity Calculation; Baseline Predictors Model proposed an itembased collaborative filtering recommendation algorithm that use the rating data to compute the similarity methods only consider the user-item behavioral data, and collaborative filtering recommendation algorithm based on neighborhood model, and uses the user portrait, item characteristics and user-item behavior data to compute characteristics and user-item behavior data to compute Collaborative filtering recommendation algorithm is to Collaborative filtering recommendation algorithm is to (3) According to the user sets prediction rating. This paper considers the user rating data from the overall recommends items that the users have rated highly but not recommends items that the users have rated highly but not recommendation algorithm on the rating data algorithm based on improved similarity computation is recommendation method based on a user's item network[J].	./cache/work_inn62q2rznhknhfgujiaek3ctm.pdf	./txt/work_inn62q2rznhknhfgujiaek3ctm.txt