Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Exploring social approach to recommend talks at research conferences

UNSPECIFIED (2012) Exploring social approach to recommend talks at research conferences. CollaborateCom 2012 - Proceedings of the 8th International Conference on Collaborative Computing: Networking, Applications and Worksharing. 157 - 164.

[img] Plain Text (licence)
Available under License : See the attached license file.

Download (1kB)

Abstract

This paper investigates various recommendation algorithms to recommend relevant talks to attendees of research conferences. We explored three sources of information to generate recommendations: users' preference about items (i.e. talks), users' social network and content of items. In order to find out what is the best recommendation approach, we explored a diverse set of algorithms from non-personalized community vote-based recommendations and collaborative filtering recommend-ations to hybrid recommendations such as social network-based recommendation boosted by content information of items. We found that social network-based recommendations fused with content information and non-personalized community vote-based recommendations performed the best. Moreover, for cold-start users who have insufficient number of items to express their preferences, the recommendations based on their social connections generated significantly better predictions than other approaches. © 2012 ICST.


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: Article
Status: Published
Date: 1 December 2012
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: CollaborateCom 2012 - Proceedings of the 8th International Conference on Collaborative Computing: Networking, Applications and Worksharing
Page Range: 157 - 164
Event Type: Conference
DOI or Unique Handle: 10.4108/icst.collaboratecom.2012.250415
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISBN: 9781936968367
Date Deposited: 22 Jul 2013 17:40
Last Modified: 07 Jan 2019 15:55
URI: http://d-scholarship.pitt.edu/id/eprint/19376

Metrics

Monthly Views for the past 3 years

Plum Analytics

Altmetric.com


Actions (login required)

View Item View Item