Enhancing Academic Event Participation with Context-aware and Social Recommendations
Advances in Social Networks Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference on, page 464--471. IEEE, (August 2012)DOI: 10.1109/asonam.2012.80
Abstract
Abstract—The plethora of talks and presentations taking place
at academic conferences makes it difficult, especially for young
researchers to attend the right talks or discuss with participants
and potential collaborators with similar interests. Participants
may not have a priori knowledge that allows them to select the
right talks or informal interactions with other participants. In
this paper we present the context-aware mobile recommendation
services (CAMRS) based on the current context (whereabouts at
the venue, popularity and activities of talks and presentations)
sensed at the conference venue. Additionally, we augment the
current context with the academic community context of conference
participants which is inferred by using social network
analysis and link prediction on large-scale co-authorship and
citation networks of participants. By combining the dynamic and
social context of participants, we are able to recommend talks
and people that may be interesting to a particular participant.
We evaluated CAMRS using data from two large digital libraries -
the DBLP and CiteSeerX, and participants from two conferences
- ICWL 2010 and EC-TEL 2011. The result shows that the new
approach can recommend novel talks and helps participants in
establishing new connections at conference venue.
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