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Power to the people: exploring neighbourhood formations in social recommender system

Published: 23 October 2011 Publication History

Abstract

The explosive growth of online social networks in recent times has presented a powerful source of information to be utilised in personalised recommendations. Unsurprisingly there has already been a large body of work completed in the recommender system field to incorporate this social information into the recommendation process. In this paper we examine the practice of leveraging a user's social graph in order to generate recommendations. Using various neighbourhood selection strategies, we examine the user satisfaction and the level of perceived trust in the recommendations received.

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Mohsen Jamali and Martin Ester. A matrix factorization technique with trust propagation for recommendation in social networks. In Proceedings of the fourth ACM conference on Recommender systems, pages 135--142, New York, NY, USA, 2010. ACM.
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Paolo Massa and Paolo Avesani. Trust-aware collaborative filtering for recommender systems. On the Move to Meaningful Internet Systems 2004, pages 492--508. Springer Berlin / Heidelberg, 2004.
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Rachael Rafter, Michael O Mahony, Neil Hurley, and Barry Smyth. What have the neighbours ever done for us? a collaborative filtering perspective. User Modeling, Adaptation and Personalization, pages 355--360. Springer Berlin / Heidelberg.
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Cited By

View all
  • (2018)Recommendations Based on Social LinksSocial Information Access10.1007/978-3-319-90092-6_11(391-440)Online publication date: 3-May-2018
  • (2017)What and who withInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2017.01.001101:C(62-75)Online publication date: 1-May-2017
  • (2016)Enhanced user modeling based on link attributes for recommendation systemProceedings of the 18th Annual International Conference on Electronic Commerce: e-Commerce in Smart connected World10.1145/2971603.2971637(1-8)Online publication date: 17-Aug-2016
  • Show More Cited By

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cover image ACM Conferences
RecSys '11: Proceedings of the fifth ACM conference on Recommender systems
October 2011
414 pages
ISBN:9781450306836
DOI:10.1145/2043932
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

Publication History

Published: 23 October 2011

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Author Tags

  1. collaborative filtering
  2. facebook
  3. recommender system
  4. social network

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RecSys '11
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RecSys '11: Fifth ACM Conference on Recommender Systems
October 23 - 27, 2011
Illinois, Chicago, USA

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Overall Acceptance Rate 254 of 1,295 submissions, 20%

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Cited By

View all
  • (2018)Recommendations Based on Social LinksSocial Information Access10.1007/978-3-319-90092-6_11(391-440)Online publication date: 3-May-2018
  • (2017)What and who withInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2017.01.001101:C(62-75)Online publication date: 1-May-2017
  • (2016)Enhanced user modeling based on link attributes for recommendation systemProceedings of the 18th Annual International Conference on Electronic Commerce: e-Commerce in Smart connected World10.1145/2971603.2971637(1-8)Online publication date: 17-Aug-2016
  • (2015)Handling cold start problem in Recommender Systems by using Interaction Based Social Proximity factor2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI)10.1109/ICACCI.2015.7275909(1987-1993)Online publication date: Aug-2015
  • (2015)Scholarly paper recommendation based on social awareness and folksonomyInternational Journal of Parallel, Emergent and Distributed Systems10.1080/17445760.2014.90485930:3(211-232)Online publication date: 1-May-2015
  • (2015)Semantic Movie RecommendationsSmart Information Systems10.1007/978-3-319-14178-7_5(125-147)Online publication date: 15-Jan-2015
  • (2013)Mining large streams of user data for personalized recommendationsACM SIGKDD Explorations Newsletter10.1145/2481244.248125014:2(37-48)Online publication date: 30-Apr-2013
  • (2013)User-centric evaluation of a K-furthest neighbor collaborative filtering recommender algorithmProceedings of the 2013 conference on Computer supported cooperative work10.1145/2441776.2441933(1399-1408)Online publication date: 23-Feb-2013
  • (2012)Inspectability and control in social recommendersProceedings of the sixth ACM conference on Recommender systems10.1145/2365952.2365966(43-50)Online publication date: 9-Sep-2012
  • (2012)Facebook single and cross domain data for recommendation systemsUser Modeling and User-Adapted Interaction10.1007/s11257-012-9128-x23:2-3(211-247)Online publication date: 19-Sep-2012
  • Show More Cited By

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