Because electronic commerce has been flourishing in recent year, the amount and the variety of information on the web have also been rapidly increasing. However, many problems occur as the result of information overload. This thesis is to study the issue of information overload in the field of multimedia that covers not only medium of diffuse knowledge but also entertainment of everyday life. The main goal of this work is to use personalized recommendation technologies to help users select multimedia he is interested in.
The thesis investigates two types of personalized recommendation: tag-based recommendation and context-aware recommendation. Regarding the former kind of recommendation, Folksonomy is the popular Web2.0 application that allows users tagging items to indicate the corresponding characteristics. These tags, provided by the users, directly or indirectly reflect his personal interests. Therefore the recommendation performance is enhanced when the tags are used with computational methods. On the other hand, the latter kind focuses on the contents and the relevant situations, because what multimedia is considered suitable for users can be different under different situations. The advantages of the personalized recommendation technology can improve performance of recommendation and take the context into account at the same time. Meanwhile this study also implements a working system for personalized multimedia recommendation.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0816109-212902 |
| Date | 16 August 2009 |
| Creators | Kuo-Li, Che |
| Contributors | Bing-Chiang Jeng, Chia-Mei Chen, Wei-Bo Lee |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0816109-212902 |
| Rights | campus_withheld, Copyright information available at source archive |
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