Open AccessResearch on Application of Collaborative Filtering Algorithm in Digital Movie Recommendation
Author(s) -
Sansan Li,
Dongxian Zhou
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1651/1/012091
Subject(s) - information overload , collaborative filtering , computer science , process (computing) , recommender system , information retrieval , information filtering system , the internet , big data , world wide web , data mining , operating system
Information overload will undoubtedly increase the time for users to search for information on the Internet. Data mining technology based on big data is constantly improving this situation. It extracts hidden, previously unknown information from massive data information to find out the internal connection between users, between the user and the item, and between items, so as to recommend information according to the user’s preferences and needs, and even provide the user with a customized page. So how does it implement personalized recommendations? This article takes online digital movie recommendation as an example, and explains the principle and process of collaborative filtering recommendation algorithm to achieve personalized recommendation through the combination of theoretical analysis and experiment.