Interpersonal relationship and recommendation are the important relation and popular mechanism. Living in the information-overloading age, the original information searching mechanisms, which require the specification of keywords, are ineffective and impractical. Moreover, a variety of recommendation techniques have been proposed and many of them have been implemented in real systems, especially in online stores. Among different recommendation techniques proposed in the literature, the content-based and collaborative filtering approaches have been broadly adopted by membership stores that maintain users¡¦ long term interest. For short-term interest, by far the content-based approach is the most popular one for recommendation. However, most of the proposed recommendation approaches do not take the social information as an important factor. In this study, we proposed several social network-based recommendation approaches that take into account the similarities of items with respect to their social closeness for meeting users¡¦ short term interests. Our experiment evaluation results show that social network-based approaches perform better than the content-based counterpart, if the user¡¦s short term interest profile contains articles of similar content. Nonetheless, content-based approach becomes better when articles in the profile are diversified in their content. Besides, contrast to content-based approach, social network-based approach is less likely to recommend articles which readers do not value. Finally, the desired articles recommended by content-based approach are very different from those by social network-based approach. This suggests the development of some hybrid recommendation method that utilizes both content and social network when making recommendations.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0804106-143419 |
| Date | 04 August 2006 |
| Creators | Liao, Yi-fan |
| Contributors | San-Yi Hwnag, Chin-Pin Wei, W.-S. Yang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0804106-143419 |
| Rights | withheld, Copyright information available at source archive |
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