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Management Science and Research

Management Science and Research is an international comprehensive professional academic journal of Ivy Publisher, concerning the development of management science technology and research, on the combination of management science theory and modern industrial technology. The main focus of the journal is the academic papers and comments of latest management science theory and method research improvement in the fields of nature science, engineering t... [More] Management Science and Research is an international comprehensive professional academic journal of Ivy Publisher, concerning the development of management science technology and research, on the combination of management science theory and modern industrial technology. The main focus of the journal is the academic papers and comments of latest management science theory and method research improvement in the fields of nature science, engineering technology, economy and science, report of latest research result in the field of material subject, aiming at providing a good communication platform to transfer, share and discuss the theoretical and technical development of management science for professionals, scholars and researchers in this field, reflecting the academic front level, promote academic change and foster the rapid expansion of management science theory and application technology.

The journal receives manuscripts written in Chinese or English. As for Chinese papers, the following items in English are indispensible parts of the paper: paper title, author(s), author(s)'affiliation(s), abstract and keywords. If this is the first time you contribute an article to the journal, please format your manuscript as per the sample paper and then submit it into the online submission system. Accepted papers will immediately appear online followed by printed hard copies by Ivy Publisher globally. Therefore, the contributions should not be related to secret. The author takes sole responsibility for his views.

ISSN Print:2326-8689

ISSN Online:2326-8727

Email:msr@ivypub.org

Website: http://www.ivypub.org/msr/

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Paper Infomation

Application of Personalized Recommendation System in Music Platform

Full Text(PDF, 105KB)

Author: Nan Sun, Borui Liu, Meiran Liu, jizhe cui

Abstract: This paper introduces the basic framework of the personalized recommendation system, the typical model of the music recommendation system and the main methods. At the same time, it analyzes the problems in the current recommendation technology and finds out the future optimization direction of the music recommendation system by discussing the solution of the problem.

Keywords: Recommended System, Content Characteristics, Collaborative Filtering

References:

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[4] DUAN Li-jun. Analysis and Comparison of User Preference Modeling methods in Service Discovery[J]. Journal of Hubei Second Teachers College, 2016, 33(2):61-64.

[5] ZHANG Yan, TANG Zhenmin, LI Yanping. Music Feature Extraction Method for Recommendation System.Computer Engineering and Applications, 2011, 47(5):130-133.

[6] LI Juan, ZHOU Mingquan, LI Peng. Music database construction based on MIDI melody feature Extraction.Computer Engineering and Applications, 2011, 47(26):124-128.

[7] David E. Hogan, Thomas Huesman. Music Training and Semantic Clustering in College Students[J]. Journal of Genetic Psychology, 2008, 169(4):322.

[8] LI Xiaolong. Research on E-commerce Personalized Recommendation Based on Map/reduce[D]. Beijing Jiaotong University, 2014.

[9] Wang Ran. Research and Implementation of Music Recommendation System Based on Mobile User's Behavior Perception[D]. Beijing University of Technology, 2016.

[10] DU Jintao. A Study on Collaborative Recommendation Model Based on Rough Set [D]. Hangzhou Dianzi University, 2009.

[11] He An. Research on Collaborative Filtering Technologies of Recommendation System for E-commerce[D]. Zhejiang University, 2007.

[12] Wang G. Survey of personalized recommendation system[J]. Computer Engineering & Applications, 2012.

[13] Cai Heng. Research on Collaborative Filtering Algorithm of Recommender Systems[D]. Jilin University, 2015.

[14] Yang Q, Pan X. Status and Development of Music Recommendation Technology[J]. Audio Engineering, 2012.

[15] Li X U. Collabrative Filtering Recommendation Based on Demography Information[J]. Journal of Anhui Science & Technology University, 2007.

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