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Prediction of Rolling Force Based on a Fusion of Extreme Learning Machine and Self Learning Model of Rolling Force Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Research of Music Recommendation System Based on User Behavior Analysis and Word2vec User Emotion Extraction

Authors : Qiuxia Li, Dan Liu

Published in: Advances in Intelligent Systems and Interactive Applications

Publisher: Springer International Publishing

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Abstract

Aiming at the recommendation accuracy, diversity and timeliness of music recommendation system, this paper puts forward the music recommendation based on user behavior analysis and user emotion extraction. User behavior analysis can analyze the music preferences, and establish user’s interest model. Collaborative filtering algorithm and user similarity calculation can be a good way to explore the user’s new interests. In addition, by analyzing user’s real-time text information in the social network. Using word2vec and clustering can help achieve the user’s real-time feeling. Combining user’s interests with user’s emotional needs, filter out the user’s current emotional music recommendation-list from the recommended music list. By this way, users get a better experience.

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Metadata
Title
Research of Music Recommendation System Based on User Behavior Analysis and Word2vec User Emotion Extraction
Authors
Qiuxia Li
Dan Liu
Copyright Year
2018
Book
Advances in Intelligent Systems and Interactive Applications

Print ISBN: 978-3-319-69095-7

Electronic ISBN: 978-3-319-69096-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-69096-4_65

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