Design And Implementation Of Music Recommendation System Based On Graph Database

Accompanied by the growing popularity of Internet technology development in recent years,the explosive growth of information on the Internet speed,so extensive information-retrieval difficulties for users,the traditional search engine technology to meet the needs of users.In the context of such prior art does not meet their needs,leading to a collaborative filtering system,and developed into a featured led research hot spots of the city.Studied music recommendations based on chart database,using collaborative filtering algorithm consists of a memory-based collaborative filtering algorithm and model-based collaborative filtering algorithm of two categories.It is based on a range of interests to the same user or project's recommendation,it references the adjacent user preference information on the target user's recommended list.Based on the comparison of the two experiments on the DataSet and choose based on cosine similarity algorithm for project correction algorithm of collaborative filtering recommender systems as part of our music.The algorithm is to a certain extent,make up for the shortcomings of traditional recommended way,also based on collaborative filtering algorithm brings certain advantages to doing a detailed analysis of the existing music recommendation system,using B/S software implements a software prototype of personalized music recommendation system as a whole.This thesis on music recommendation system for evaluation of user satisfaction,and the availability of the system were tested.Through the assessment of the results we found that the overall performance of the system,to a certain extent,effectively recommending the user might be interested in the results,and the system can fulfill the expectation.