隨著全球資訊網的蓬勃發展，我們可以在網路上取得大量的音樂資料。為了替使用者尋找其想要的音樂物件，發展相關的推薦服務便是迫切需要的。在本篇論文中，我們設計了一個音樂推薦系統來提供使用者個人化的音樂推薦服務。在這個音樂推薦系統中的音樂物件是採用MIDI的格式，對於每個以複音型態存在的音樂物件，我們會先挑選出這個音樂物件中具有代表性的音軌，再從這個音軌中擷取出六種不同的特徵。根據這些特徵，系統就可以將音樂物件加以分群。對於使用者來說，系統會分析使用者的瀏覽歷史以取得使用者的興趣。根據使用者喜好每個音樂群組的程度，我們提出三種不同的推薦方法以滿足使用者的需求。最後我們提出實驗的結果來證明我們系統中所採用的方式是可行的。

With the growth of the World Wide Web, a large amount of music data is available on the Internet. In addition to searching expected music objects for users, it becomes necessary to develop a recommendation service. In this paper, we design the Music Recommendation System (MRS) to provide a personalized service of music recommendation. The music objects of MIDI format are first analyzed. For each polyphonic music object, the representative track is first determined, and then six features are extracted from this track. According to the features, the music objects are properly grouped. For users, the access histories are analyzed to derive user interests. The content-based, collaborative and statistics-based recommendation methods are proposed, which are based on the favorite degrees of the users to the music groups. A series of experiments are carried out to show that our approach is feasible.

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