Ontology-Based Context Awareness Music Recommendation

碩士 === 輔仁大學 === 資訊管理學系 === 97 === In the ubiquitous computing environment, the context information around users can be detected by the mobile equipments like cell phone, PDA, or notebook at any moment. From this background, context-awareness means detecting the context information by sensors, like G...

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Bibliographic Details
Main Authors: Hsiang-Yi Hung, 洪湘貽
Other Authors: Sung-Shun Weng
Format: Others
Language:zh-TW
Published: 2008
Online Access:http://ndltd.ncl.edu.tw/handle/79156182417615840354
Description
Summary:碩士 === 輔仁大學 === 資訊管理學系 === 97 === In the ubiquitous computing environment, the context information around users can be detected by the mobile equipments like cell phone, PDA, or notebook at any moment. From this background, context-awareness means detecting the context information by sensors, like GPS, RFID, monitors to know the location, temperature or the time about the user on the moment. Then, it would provide the suitable information or service according to the different context to meet the users’ demands. Therefore, using the technique of context-awareness to acquire user information as an index to recommend the information can make the result closer to the users’ habits and preferences and more suitable information and services to user to achieve the goal of personal recommendation. This research applied the concept of the context ontology to build a context -awareness music recommendation system that recommends the music according to the users’ current context. By the characteristic of ontology, it can express the interactive knowledge between people and environments, and help to analyze the users’ current context. Then, by analyzing the music listening history to know the users’ music preferences in different context, the system would recommend the similar type of music to users to let them listen to different kinds of music as they want in different contexts. In order to validate the precision of music recommendation, we recruited fifty participants in this research. And the experiment results showed that the precision of music recommendation can achieve 75% no matter the context is the same or different. Besides, whether the users’ music preferences affected by contexts or not, it did not affect the precision. In conclusion, this research built a context-awareness music recommendation system based on ontology, which is validated it can recommend the music according to the users’ current context. Using context as the index of recommendation, it can help the result meet the users’ demands, save the time of searching music, and increase the quality of listening to music.