计算机科学 ›› 2018, Vol. 45 ›› Issue (6): 76-83.doi: 10.11896/j.issn.1002-137X.2018.06.013
朱文强
ZHU Wen-qiang
摘要: 移动通信技术的飞速发展和广泛应用,促进了移动社交网络和O2O服务的高度融合。在订购O2O服务时,人们已习惯先通过移动社交网络咨询O2O服务信息;待服务完成后,再通过移动社交网络发表对O2O服务的体验感受。由于移动社交网络具有开放性和匿名性,用户需要有效识别出可信的用户群体,以对这些服务体验和反馈信息的可靠性进行核实。目前,可信群体识别方面的研究主要集中在云计算和在线社交网络领域,且大多采用全局信任的计算方式,未考虑用户的个性化信任因素,无法适用于面向O2O服务的个性化移动社交网络。针对这一问题,对Advogato信任模型进行扩展,考虑用户的互动程度、社交圈子相似性及兴趣相似性,采用信任容量优先最大流搜索方法建立用户的个性化信任网络,并将识别出的可信用户群体排序输出。基于真实数据集的实验结果表明,该模型在可信群体预测的准确度、漏检率及Top排序范围方面比现有方法的效果更优。
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