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A personalized people recommender system using global search approach

Tsai, Chun-Hua and Brusilovsky, Peter (2016) A personalized people recommender system using global search approach. In: IConference 2016, 20 March 2016 - 23 March 2016, Philadelphia, Pennsylvania, USA.

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The goal of people recommender system is to generate meaningful social suggestion to users. The abundant data are the key factor in fulfilling a recommendation task, but the cost of user data in a real-world system is high. In this paper, we propose a novel approach that integrates a global search result with a personalized people recommendation system. Our approach utilizes the user identity as a query keyword and processes the search results through five different customized parsers. This approach solves the cold-start issue in recommendation systems and leverages the cross-domain information in order to provide a better recommendation result. To test our approach, we embedded it into an existing conference navigator system then deployed the system at two international conferences. The survey results indicate largely positive feedback about the system's effectiveness. Our study results also shed some light on the social interactions that take place at an academic conference.


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Item Type: Conference or Workshop Item (Poster)
CreatorsEmailPitt UsernameORCID
Tsai, Chun-Hua
Brusilovsky, Peterpeterb@pitt.eduPETERB0000-0002-1902-1464
Date: 8 March 2016
Date Type: Publication
Journal or Publication Title: IConference 2016 Proceedings
Event Title: IConference 2016
Event Dates: 20 March 2016 - 23 March 2016
Event Type: Conference
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
Date Deposited: 27 Jul 2016 19:44
Last Modified: 01 Nov 2017 12:57


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