隨著數位閱讀時代的來臨，數位內容平台也相繼誕生。由於數位閱讀載具的限制，數位內容使用者對於智慧化、個人化的需求也隨著提昇。本文提出一個融合使用者導向分析及內容關聯導向分析的個人化數位內容推薦技術。數位內容平台(如：電子書城)透過呼叫個人化推薦引擎，提供個人化搜尋或推薦服務。本文所提之個人化數位內容推薦技術考量數位內容之內容關聯性以及使用者的偏好， 讓使用者能夠快速搜尋到其所感興趣的內容， 或獲得其感興趣的推薦項目。

With the coming of digital reading era, digital content platforms have also being emerging. Because of the limitation of reading devices, the need of intelligent and personalized services for digital content users is
increasing. This paper presents a personalized recommendation technique considering user-based analysis and content-based analysis for digital content. A digital content platform (ex. e-book store) can provide
personalized search services or personalized recommendation services by requesting our personalized recommendation engine. The proposedpersonalized recommendation technique takes the digital content
association and user preference into consideration. Based on this recommendation mechanism, users can find the digital contents or get recommended items which they are interested in more easily.