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| Group Recommendation in Social Networks Based on Influence Spread |
| Ye Jiaxin, Xiong Huixiang, Yi Ming, Liu Ming |
| School of Information Management, Central China Normal University, Wuhan 430079 |
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Abstract In social networks, providing personalized recommendation services for group users can effectively improve recommendation efficiency. When conducting group recommendation, most of the existing studies only consider the interests of the user group, but ignore the mutual influence between users in the group. To this end, this paper proposes a social network group recommendation method based on influence spread. Considering the user's own interests and those generated by the influence of core users, the social network group recommendation service is carried out. To prove the effectiveness of the proposed method, data on Weibo “Super Talk” are taken as an example to verify the method. Experiments indicate that combining influence spread can significantly improve the effect of group recommendation.
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Received: 12 July 2021
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