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Tech Report kmi-05-13 Abstract


BuddyFinder-CORDER: Leveraging Social Networks for Matchmaking by Opportunistic Discovery
Techreport ID: kmi-05-13
Date: 2005
Author(s): Jianhan Zhu, Marc Eisenstadt, Alexandre Goncalves, Chris Denham
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Online social networking tools are extremely popular, but can miss potential discoveries latent in the social 'fabric'. Matchmaking services can do naive profile matching with old database technology, and modern ontological markup, though powerful, can be onerous at data-input time. In this paper, we present a system called BuddyFinder-CORDER which can automatically produce a ranked list of buddies to match a user's search requirements specified in a term-based query, even in the absence of stored user-profiles. We integrate an online social networking search tool called BuddyFinder with a text mining method called CORDER to rank a list of online users based on 'inferred profiles' of these users in the form of scavenged Web pages.

Publication(s):

To appear in Proc. of International Semantic Web Conference (ISWC2005) Workshop on Semantic Network Analysis, November 7, 2005, Galway, Ireland.
 
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Social Software is...


Social Software
Social Software can be thought of as "software which extends, or derives added value from, human social behaviour - message boards, musical taste-sharing, photo-sharing, instant messaging, mailing lists, social networking."

Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.