Abstract
Many systems have been developed to support people in forming communities and communicating with others in the communities. However, community support systems are not only concerned with community formation and communication. Namely, they give people the chance to make use of the communities for personal activities, e.g., they can use other members’ knowledge to select information items that are high in quality and conform to the user’s individual tastes. Collaborative filtering is a recommendation method that utilizes evaluations given by other users, and is therefore useful for users to obtain desired and relevant information items in a community. In this paper, we present an agent architecture of a community support system with a collaborative filtering method to recommend appropriate information items to users.
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Funakoshi, K., Kamei, K., Yoshida, S., Kuwabara, K. (2001). Incorporating content-based collaborative filtering in a community support system. In: Yuan, S.T., Yokoo, M. (eds) Intelligent Agents: Specification, Modeling, and Applications. PRIMA 2001. Lecture Notes in Computer Science, vol 2132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44637-0_14
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DOI: https://doi.org/10.1007/3-540-44637-0_14
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