摘要
电影作为海量信息的一个重要载体,存在信息过载问题,因此将推荐算法应用于电影推荐具有重大意义。文中主要研究基于协同过滤算法的电影推荐系统,该系统主要由三部分组成,包括前台的电影界面展示、系统的推荐算法以及后台数据集;首先,该系统通过网络爬虫爬取与电影相关的数据;其次,通过协同过滤算法过滤出用户感兴趣的电影;最后,通过图形用户界面进行数据交互,针对数据集中的用户推荐数据集中的相关电影,系统最终的运行结果与预期呈现的结果基本一致。
Movie is served as an important carrier of massive information,and has the problem of information overload.Therefore,it has great significance for applying the recommendation algorithm to movie recommendation.This topic mainly studies the movie recommendation system based on collaborative filtering algorithm,which is mainly composed of three parts,icluding the foreground movie interface display,the system recommendation algorithm and the background data set.The system crawls data related to movies through web crawler,filters out movies that users are interested in through collaborative filtering algorithm,and finally carries out data interaction through graphical user interface to recommend related movies in data set for users in data set,the final results of the system are similar to the expected results.
作者
邢艳芳
XING Yan-fang(Communication University of China,Nanjing 211172,China)
出处
《信息技术》
2025年第5期9-14,共6页
Information Technology
基金
2023年校级教学改革研究项目(JG202305)
2023年教育部第二期供需对接就业育人项目(202301-03787)
2022全国高等院校计算机基础教育研究会计算机基础教育教学研究项目(2022-AFCEC-093)。
