利用隱含式使用者回饋產生時間相依的個人化音樂播放清單

Time-dependent Personalized Music Playlist Generation from Implicit User Feedback

魏吟軒(Yin-Hsuan Wei)

指導教授 ： 林守德

國立臺灣大學/電機資訊學院/資訊工程學研究所/碩士(2011年)

https://doi.org/10.6342/NTU.2011.01268

摘要

無資料

關鍵字

音樂推薦 ； 時間相依之播放清單

並列摘要

Recommendation is essential to the issue of information overload. Many literatures have proposed great models for this problem, but the majority still focuses on explicit rating data. Due to the characteristics of music, we think that implicit user feedback is more valuable and useful. In this thesis, we process the problem of recommendation in a different aspect, out of the ordinary matrix factorization or k-nearest neighbor methods. We treat recommendation as a binary classification and ranking problem, and apply features covering three parts: global, cluster-based, and temporal features. Moreover, we merge recommendation into playlist because ranking by scores is not suitable for listening. When it comes to playlist generation, most previous approaches just consider whether the playlist is smooth. However, people often listen to music when engaging in another activity, so we believe a good playlist should also be time-dependent and personalized. To achieve this goal, we construct a temporal Bayesian network to mine the listening pattern at specific time for each user. Besides, putting obvious and non-obvious recommendations together in playlist can balance the familiarity and novelty, and let it more attractive to listeners.

並列關鍵字

music recommendation ； time-dependent playlist generation

參考文獻

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[4] Y. Koren, R. Bell, and C. Volinsky: “Matrix Factorization Techniques for Recommender Systems,” IEEE Computer, Vol. 42, Issue. 8, pp. 30–37, 2009.

[5] S. Rendle, and L. Schmidt-Thieme: “Online-Updating Regularized Kernel Matrix Factorization Models for Large-Scale Recommender Systems,” ACM Conference on Recommender Systems, pp. 251–258, 2008.

[6] Y. Koren: “Collaborative Filtering with Temporal Dynamics,” International Conference on Knowledge Discovery and Data Mining, pp. 447–456, 2009.