Abstract
Locating experts or work partners in large communities can sometimes be hard. The most common way of accomplishing this task is through recommendations from known acquaintances. This networked search for others who fit required profiles is a form of social navigation. However, needs, interests and expertise change rapidly, so time is an important factor in this type of situation, and recommendations need to be time-sensitive. This paper presents a peer-to-peer system for social network navigation, which builds user profiles through a temporal analysis of ongoing activities and matches these to find opportunities for collaboration.
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Vivacqua, A.S. et al. (2008). Temporal Profiling for Opportunistic Partnership Recommendation. In: Shen, W., Yong, J., Yang, Y., Barthès, JP.A., Luo, J. (eds) Computer Supported Cooperative Work in Design IV. CSCWD 2007. Lecture Notes in Computer Science, vol 5236. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92719-8_4
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DOI: https://doi.org/10.1007/978-3-540-92719-8_4
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