Personalizing Information Using Users’ Online Social Networks: A Case Study of CiteULike
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This paper aims to assess the feasibility of a new and less-focused type of online sociability (the watchingnetwork) as a useful information source for personalized recommendations. In this paper, we recommendscientific articles of interests by using the shared interests between target users and their watchingconnections. Our recommendations are based on one typical social bookmarking system, CiteULike. Thewatching network-based recommendations, which use a much smaller size of user data, produces suggestionsthat are as good as the conventional Collaborative Filtering technique. The results demonstrate that thewatching network is a useful information source and a feasible foundation for information personalization. Furthermore, the watching network is substitutable for anonymous peers of the Collaborative Filteringrecommendations. This study shows the expandability of social network-based recommendations to the newtype of online social networks.
Abstract
This paper aims to assess the feasibility of a new and less-focused type of online sociability (the watchingnetwork) as a useful information source for personalized recommendations. In this paper, we recommendscientific articles of interests by using the shared interests between target users and their watchingconnections. Our recommendations are based on one typical social bookmarking system, CiteULike. Thewatching network-based recommendations, which use a much smaller size of user data, produces suggestionsthat are as good as the conventional Collaborative Filtering technique. The results demonstrate that thewatching network is a useful information source and a feasible foundation for information personalization. Furthermore, the watching network is substitutable for anonymous peers of the Collaborative Filteringrecommendations. This study shows the expandability of social network-based recommendations to the newtype of online social networks.
참고문헌 (68)
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