Socially-Aware Venue Recommendation for Conference Participants
release_p5qdbvoptzhszi63q2pkrrw3jm
by
Feng Xia, Nana Yaw Asabere, Joel J.P.C. Rodrigues, Filippo Basso,
Nakema Deonauth, Wei Wang
2013
Abstract
Current research environments are witnessing high enormities of presentations
occurring in different sessions at academic conferences. This situation makes
it difficult for researchers (especially juniors) to attend the right
presentation session(s) for effective collaboration. In this paper, we propose
an innovative venue recommendation algorithm to enhance smart conference
participation. Our proposed algorithm, Social Aware Recommendation of Venues
and Environments (SARVE), computes the Pearson Correlation and social
characteristic information of conference participants. SARVE further
incorporates the current context of both the smart conference community and
participants in order to model a recommendation process using distributed
community detection. Through the integration of the above computations and
techniques, we are able to recommend presentation sessions of active
participant presenters that may be of high interest to a particular
participant. We evaluate SARVE using a real world dataset. Our experimental
results demonstrate that SARVE outperforms other state-of-the-art methods.
In text/plain
format
Archived Files and Locations
application/pdf 1.3 MB
file_eky3qzdcuzclnpz7gvmq4jhzwi
|
arxiv.org (repository) web.archive.org (webarchive) |
1312.6808v1
access all versions, variants, and formats of this works (eg, pre-prints)