Experience Discovery: hybrid recommendation of student activities using social network data

HetRec '11 Pub Date : 2011-10-27 DOI:10.1145/2039320.2039327
R. Burke, Yong Zheng, Scott Riley
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引用次数: 14

Abstract

The aim of the Experience Discovery project is to recommend extracurricular activities to high school and middle school students in urban areas. In implementing this system, we have been able to make use of both usage data and data drawn from a social networking site. Using pilot data, we are able to show that very simple aggregation techniques applied to the social network can improve recommendation accuracy.
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体验发现:利用社交网络数据对学生活动进行混合推荐
体验发现项目的目的是向城市地区的高中生和中学生推荐课外活动。在实现该系统的过程中,我们已经能够利用使用数据和从社交网站获取的数据。使用试验数据,我们能够证明将非常简单的聚合技术应用于社交网络可以提高推荐的准确性。
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Experience Discovery: hybrid recommendation of student activities using social network data A kernel-based approach to exploiting interaction-networks in heterogeneous information sources for improved recommender systems Expert recommendation based on social drivers, social network analysis, and semantic data representation Matrix co-factorization for recommendation with rich side information and implicit feedback Information market based recommender systems fusion
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