Open AccessField-aware User Influence Recommendation Model Based on Trust Relationship
Author(s) -
Yun Bai,
Weiquan Cai
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1453/1/012055
Subject(s) - computer science , field (mathematics) , reliability (semiconductor) , user modeling , node (physics) , data mining , order (exchange) , human–computer interaction , user interface , engineering , mathematics , pure mathematics , power (physics) , physics , structural engineering , finance , quantum mechanics , economics , operating system
In current determining of user influence based on network structure, the overall importance of user node in network usually attracts great attention. However, the significance of the users in specific field has not been fully studied, which result in low accuracy and reliability in user influence measurement. In order to resolve these problems, this research proposes a field-aware user influence model, which constructs user influence for specific fields, and analyses the global influence of users in the whole network on a network structure basis. The model, assisted by historical behaviour data, not only considers the spread of user influence, but also takes the relationship between user influence and fields into account. Referring to the global influence, the model is able to optimize the composition of user influence, and further improve the accuracy of recommendation. The experiments based on real data sets conducted in this research unexceptionally proved that the field-aware user influence model proposed in this paper, compared with other methods, can effectively improve the recommendation accuracy.