WANG Jing, ZHAO Hui, LIU Zhijing. Exploring User Influence for Topical Group Recommendation[J]. Chinese Journal of Electronics, 2017, 26(1): 106-111. doi: 10.1049/cje.2016.11.017
Citation: WANG Jing, ZHAO Hui, LIU Zhijing. Exploring User Influence for Topical Group Recommendation[J]. Chinese Journal of Electronics, 2017, 26(1): 106-111. doi: 10.1049/cje.2016.11.017

Exploring User Influence for Topical Group Recommendation

doi: 10.1049/cje.2016.11.017
Funds:  This work is supported by the National Natural Science Foundation of China (No.61202177) and the Fundamental Research Funds for the Central Universities (No.7214572801).
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  • Corresponding author: ZHAO Hui (corresponding author) was born in 1983. He received the B.E. and M.S. degrees in computer science and technology from Xidian University in 2005 and 2008. His research interests include recommendation system and personalized recommendation for m-learning. (Email:sheen.zhao@hotmail.com)
  • Received Date: 2014-12-11
  • Rev Recd Date: 2015-10-10
  • Publish Date: 2017-01-10
  • With the development of social networks, many recommendation systems recommend items to a group of users, known as group recommendation. However, it will not be an appropriate recommendation without user topical influence analysis. We proposed a new group recommendation based on user topical influence analysis. We firstly construct several topical sub-groups depending on topics. Then we analyze user topical influence in sub-group, including user influence on specific topic and the topical sub-group. Besides, four user-factors are introduced to calculate the user social influence on topical sub-groups more accurately. Based on user topical influence analysis, we present our topical group recommendation algorithm, which calculates the predicted rating value for sub-group by aggregating weighted ratings of all users in the sub-group. The experimental results show convincingly that our proposed method can improve the group recommendation quality.
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