以情緒為基礎之情境式音樂推薦系統

A Context-Aware Music Recommendation System Based On Emotion

王宇頎(Yu-chi Wang)

指導教授 ： 曹承礎

國立臺灣大學/管理學院/資訊管理學研究所/碩士(2008年)

https://doi.org/10.6342/NTU.2008.00847

摘要

隨著網際網路的發展以及音樂創作的普及，音樂推薦系統成為主要發展中的應用服務之一，嘗試提供符合使用者需求或心情的音樂。為了達成這個目標，傳統的推薦技術被廣泛的使用在這個領域，大部分現有的音樂推薦系統專注在探索使用者偏好、META-DATA、聆聽紀錄、以及音樂的內容來產生可能讓使用者滿意的個人化音樂推薦功能。
然而，聆聽紀錄是一種主題式的心理認知經驗，這種經驗會在特殊的時間點與個人意向高度相關，因此，情境因素諸如時間、地點、氣候、與溫度等常被納入推薦系統中來增加推薦結果的精確性；心理因素是另一個影響使用者對推薦結果滿意度的重要因素。
有鑑於此，本研究結合音樂聆聽者的情感因素與情境資訊，先依據Kate Hevner的情緒循環模型、ConceptNet的語意網、以及音樂學原理，計算在使用者、情緒、與情境等因素間的相似度，做為共通性的音樂基礎；再依照使用者的音樂偏好、聆聽音樂時的行為、以及使用者回報的資訊，透過以使用者為基礎的協同過濾演算法，找出不同使用者對音樂的個人差異，來建構一更為符合使用者情境與情緒因素的音樂推薦系統。

關鍵字

推薦系統 ； 情緒 ； 協同過濾 ； 音樂 ； 情境

並列摘要

Music recommendation systems are emerging applications that attempt to provide music to suit users’ needs or moods. To achieve this goal, traditional recommendation techniques are widely used in this field. Most of the music recommendation system exploits user interest, metadata, listening history, and audio signals of music to generate a personalized function that can predict songs the user may like.
However, listening experience is a type of subjective cognitive experience that is highly dependent on the individual’s intention at a particular time. Thus, contexts such as time, location, weather, and temperature have been added to systems to improve their accuracy. Psychological influences represent another important aspect that determines the user’s satisfaction with the recommended results.
In the proposed approach, listeners’ emotional information is used in conjunction with context information. We first gather the explicit similarity between human, emotion, context, and music based on Kate Hevner’s Adjective Cycle, the semantic network of ConceptNet, and musicology as the common fundamental. Then, we adjust the individual differences according to the user’s musical taste, listening behavior, and feedback through user-based collaborative filtering in order to generate a more individual intentional music recommendation system.

並列關鍵字

recommender system ； emotion ； context ； collaborative filtering ； music

參考文獻

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