由於網路科技日新月異，使得數位內容之交換越來越容易，但所引發的著作權問題卻不斷受爭議，也間接顯示出著作權法之不足。Lawrence Lessig有鑑於此，提出創用CC(Creative Commons)的觀念，希望可以提供創作者另一個新的管道來分享其創作，卻也同時可以保留其部分權利(Some Rights Reserved)。但目前資訊共享創作僅在主從式(Client-Server)架構中提供較完整的服務。本論文將指出資訊共享創作架構在主從式網路之缺點，並提出一個在Super node對等式(Peer-to-Peer,P2P)網路上具CC授權的數位內容共享創作之平台，且使用結合了各式本體論(Ontology)及規則(Rule)之SWRL (Semantic Web Rule Language)來加強目前資訊共享創作上之表示及推論。 / Owing to network technology changing, it gets easier and easier to exchange digital contents. However, the emerging copyright problems dispute shows the deficiency of copyright. Lawrence Lessig proposed Creative Commons (CC), the concept of providing another new channel for creators to share their creative works by keeping some rights reserved. In this thesis, we indicate the shortcomings of CC on Client-Server network and present a rights description control system to share digital contents with CC licenses on Super-node P2P network. We use ontology and rule e.g. SWRL (Semantic Web Rule Language) to enhance CC’s digital rights description and control on the P2P network.

推薦系統目的在於收集大眾對於資源的評價，經過推薦機制的整理，呈現給符合偏好的使用者，但是Supernode架構與傳統主從架構的不同，增加推薦系統收集、統計推薦指標的困難。在本篇論文中，將利用RDF(S)建置與Supernode、Peer、MP3相關的本體論，同時，依據Supernode與Peer在推薦系統中所扮演的功能與角色的不同，將不同的結構藍圖分別放置在Supernode與Peer之中，並且藉由Supernode與Peer中所描述的資源、屬性以及資源和資源之間的關係來解決在Supernode架構中推薦指標的收集、統計與更新等問題，以及降低推薦系統中"Cold Start"與"Spamming"這兩個問題所產生的影響。 / The purpose of recommendation system is to collect public opinions and provide synthetic recommended result for users. Using our proposed recommended mechanism, the recommendation system presents personal music recommended list for each user in peer node to match his preference. Because the complexity difference of network structure, we found that the rating collection and computation process will be more complex in supernode P2P network than in client-server WWW network. In this thesis, firstly we use RDF(S) to construct associated ontology schema for supernode, peer node, and MP3 music. Then, we put respective ontology schema in the suprenode and peer node based on their roles and functions within the recommendation system. The resources and attributes relationships between supernode and peer nodes provide the capacity to solve the rating collection, analysis, and updating problems. We also propose possible solutions for reducing the side effects of cold start and spamming problems in the recommendation system.