Issue |
JNWPU
Volume 37, Number 6, December 2019
|
|
---|---|---|
Page(s) | 1294 - 1301 | |
DOI | https://doi.org/10.1051/jnwpu/20193761294 | |
Published online | 11 February 2020 |
Recommendation Model for Trust Circle Mining Based on Users' Interest Fields
基于用户兴趣领域中可信圈挖掘的推荐模型
School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an 710072, China
Received:
27
February
2019
A trust-based recommendation system recommends the resources needed for users by system rating data and users' trust relationship. In current relevant work, an over-generalized trust relationship is likely to be considered without exploiting the relationship between trust information and interest fields, affecting the precision and reliability of the recommendation. This research, therefore, proposes a users' interest-field-based trust circle model. Based on different interest fields, it exploits potential implicit trust relationships in separated layers. Besides, it conducts user rating by combining explicit trust relationships. This model not only considers the matching between trust information and fields, but also explores the implicit trust relationships between users do not revealed in specific fields, thus it is able to improve the precision and coverage of rating prediction. The experiments made with the Epinions data set proved that the recommendation model based on trust circle exploiting in users' interest fields proposed in this research, is able to effectively improve the precision and coverage of the recommendation rating prediction, compared with the traditional recommendation algorithm based on generalized trust relationship.
摘要
基于信任的推荐系统通过系统评分数据和用户信任关系为用户推荐所需资源。现有相关工作中在考虑信任关系时,通常考虑的是一种泛化的信任关系,尚未充分挖掘信任关系信息与特定兴趣领域之间的关系,对推荐的准确性和可靠性会产生一定的劣化影响。考虑到以上问题,提出基于用户兴趣领域的信任圈模型,针对不同兴趣领域分层挖掘用户间潜在的隐形信任关系;并充分融合显性信任关系为用户资源进行综合评分。该模型不仅考虑信任信息与领域的匹配关系,而且能够挖掘在具体领域下用户间的隐性信任关系,能够进一步提高评分预测的精确度和覆盖率。通过在Epinions数据集上的实验,证明了所提出的基于用户兴趣领域可信圈挖掘的推荐模型与基于泛化信任关系的传统推荐算法相比可以有效提高推荐评分预测的准确度和覆盖率。
Key words: trust relationship / interest field / recommendation algorithm / trust circle / social network
关键字 : 信任关系 / 兴趣领域 / 推荐算法 / 可信圈 / 社会网络
© 2019 Journal of Northwestern Polytechnical University. All rights reserved.
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