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Online Friend Recommendation through Personality Matching and Collaborative Filtering

Authors:
Li Bian
Henry Holtzman

Keywords: Collaboratie filterin; Friend recommendation; Social network; Reality projection; Social TV

Abstract:
Most social network websites rely on people’s proximity on the social graph for friend recommendation. In this paper, we present MatchMaker, a collaborative filtering friend recommendation system based on personality matching. The goal of MatchMaker is to leverage the social information and mutual understanding among people in existing social network connections, and produce friend recommendations based on rich contextual data from people’s physical world interactions. MatchMaker allows users’ network to match them with similar TV characters, and uses relationships in the TV programs as parallel comparison matrix to suggest to the users friends that have been voted to suit their personality the best. The system’s ranking schema allows progressive improvement on the personality matching consensus and more diverse branching of users’ social network connections. Lastly, our user study shows that the application can also induce more TV content consumption by driving users’ curiosity in the ranking process.

Pages: 230 to 235

Copyright: Copyright (c) IARIA, 2011

Publication date: November 20, 2011

Published in: conference

ISSN: 2308-4278

ISBN: 978-1-61208-171-7

Location: Lisbon, Portugal

Dates: from November 20, 2011 to November 25, 2011