Abstract
When one joins an existing community, she or he may have little-to-no knowledge of what other members already know. “Traditional” and electronic media are useful to collect information, but when the request is related to social experience, it is hard to locate and extract social knowledge from essentially subjective individual accounts. Asking somebody would then be a better way to search information, but it has disadvantages, too: the practicable area of potential contacts is limited by the range of one’s personal network, the contacted individuals’ knowledge, time limitations, etc. Communication on a personal basis in a new community is always trial-and-error driven, and it does not guarantee obtaining the information of interest even when such information is freely available from some of the community members. As a result of this, newcomers usually experience significant difficulties in adaptation to the community. In an attempt to help overcome this problem, the presented study proposes a system to assist personalized knowledge sharing. The system allows the user to navigate a social space of a community and to locate members who would address the user’s needs.
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References
Walter, F.E., Battiston, S., Schweitzer, F.: A Model of a Trust-based Recommender System on a Social Network. In: Autonomous Agents and Multi-Agent Systems, pp. 57–74 (2008)
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© 2008 Springer-Verlag Berlin Heidelberg
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Kumokawa, S., Kryssanov, V.V., Ogawa, H. (2008). SoNa: A Multi-agent System to Support Human Navigation in a Community, Based on Social Network Analysis. In: Prendinger, H., Lester, J., Ishizuka, M. (eds) Intelligent Virtual Agents. IVA 2008. Lecture Notes in Computer Science(), vol 5208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85483-8_64
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DOI: https://doi.org/10.1007/978-3-540-85483-8_64
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85482-1
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