首页> 外文会议>Proceedings of the 45th Annual Hawaii International Conference on System Sciences >Peer-Based Recommendations in Online B2C E-Commerce: Comparing Collaborative Personalization and Social Network-Based Personalization
【24h】

Peer-Based Recommendations in Online B2C E-Commerce: Comparing Collaborative Personalization and Social Network-Based Personalization

机译:在线B2C电子商务中基于对等方的建议:比较协作个性化和基于社交网络的个性化

获取原文
获取原文并翻译 | 示例

摘要

With the widespread diffusion of social network platforms, e-vendors can now use social network information to provide personalized services to their consumers. Nonetheless, the accuracy of social network-based personalization remains uncertain, as compared to that of traditional personalization approaches. Drawing on social influence and similarity attraction theories, this study compares social network-based personalization with the traditional peer-based personalization approach of collaborative personalization. We report results of a preliminary within subject experiment of 29 subjects belonging to a single social network. Our findings indicate that social network-based personalization can provide accurate personalized offerings. These are as accurate as those of collaborative personalization when within the specific product category on which collaborative personalization is based and better than collaborative personalization when outside the specific category.
机译:随着社交网络平台的广泛传播,电子供应商现在可以使用社交网络信息为其消费者提供个性化服务。但是,与传统的个性化方法相比,基于社交网络的个性化的准确性仍然不确定。利用社会影响力和相似性吸引理论,本研究将基于社交网络的个性化与传统的基于对等体的协作个性化方法进行了比较。我们报告了属于单个社交网络的29个主题的主题实验的初步结果。我们的发现表明,基于社交网络的个性化可以提供准确的个性化产品。当在协作个性化所基于的特定产品类别中时,这些精度与协作个性化的准确性一样,并且比在特定类别之外时的协作个性化更好。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号