文章基本信息

标题：Recommendation System for Music File
本地全文：下载
作者：Tuhina Sultana ; Nikita Sharma ; Sunil Aher 等
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2015
卷号：6
期号：1
页码：275-277
出版社：TechScience Publications
摘要：Recommender systems are mostly implemented in E-commerce website to help users or customers for finding those items which are liked by them. A recommender system should be so efficient that it should provide data for customers which interest them. The recommendation system provides an innovative recommendation for music data that combines two important aspects that are the interactive genetic algorithm and the content based filtering technique. The recommendation system tries to analyse data used by users and recommends those items which might interest the users or customers. This system provides recommendation depending on user profile. Today there is an increase number of users turning into computation recommender systems. With increasing number of customers and websites system aims to support everyday process of recommendation.
关键词：Recommender System; User’s preference; Music;Extraction; Interactive genetic algorithm; Content based;filtering; Cross Over