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首页> 外文期刊>Knowledge-Based Systems >A novel group recommender system based on members' influence and leader impact
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A novel group recommender system based on members' influence and leader impact

机译：基于成员影响和领导者影响的新型集团推荐系统

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摘要

Group recommender systems have been designed which, instead of suggesting one or more items to people individually, concurrently recommend them to a group of people who have a common interest, with a view to satisfying each of them. One of the most important issues in these systems is social relationships and the influence of individuals on each other in groups. In this article, a new method has been proposed to compute members' influence on each other based on similarity and trust. Normally in groups, there are some people called Leaders who are trusted more than other members and have a significant impact on the members. Therefore, this study has attempted to compute the leader's impact on the members' preferences. One remarkable aspect of this method is the use of a combination of fuzzy clustering and similarity measure to find users who have similar interests. Furthermore, an implicit trust metric has been formulated to improve the efficiency of the influence process and leader identification. Eventually, the proposed method which has been evaluated utilizing a MovieLens 1001k dataset showed significant results by MAE, RMSE, Precision, and a group-satisfactionmeasure compared to state-of-the-art techniques. Further, the proposed trust metric has shown better efficiency compared to some state-of-the-art methods. (C) 2020 Elsevier B.V. All rights reserved.
机译：集团推荐系统已经设计，而不是单独向人们建议一个或多个项目，同时推荐给一群具有共同兴趣的人，以满足他们每个人。这些系统中最重要的一个问题之一是社会关系以及各组中的个人对彼此的影响。在本文中，已经提出了一种基于相似性和信任来计算成员对彼此的影响。通常在群体中，有些人称之为相信其他成员的领导者，对成员产生重大影响。因此，这项研究试图计算领导者对成员偏好的影响。这种方法的一个显着方面是使用模糊聚类和相似度量的组合来查找具有相似兴趣的用户。此外，已经配制了隐式信任度量以提高影响过程和领导者识别的效率。最终，与最先进的技术相比，利用Movielens 1001K数据集进行了评估的所提出的方法，显示了MAE，RMSE，精度和组满意度的显着结果。此外，与某些最先进的方法相比，所提出的信任度量表现出更好的效率。 （c）2020 Elsevier B.v.保留所有权利。

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