协同过滤
聚类分析
过程(计算)
鉴定(生物学)
集合(抽象数据类型)
计算机科学
社会化媒体
推荐系统
社交网络(社会语言学)
万维网
数据挖掘
情报检索
数据科学
机器学习
植物
生物
程序设计语言
操作系统
作者
Jia-Li Chang,Hui Li,Jian-Wu Bi
标识
DOI:10.1080/13683500.2021.2014792
摘要
This study proposes a hybrid method for producing personalized travel recommendation that better meet travellers’individual needs and also improve their online booking experience. The proposed method integrates multi-attribute collaborative filtering with social network analysis within the framework of large-scale group decision-making. It includes four modules, i.e. identification of online opinion experts, construction of a social network, detection of user communities, and interactively produced of personalized travel recommendation. Specifically, the preliminary user filtering and k-means clustering approach are utilized to identify the online opinion experts for a specific travel recommendation issue. Then, social network construction and its community detection process are adopted to alleviate the sparsity problem. Finally, the travel alternatives are ranked to select recommendations, and this is done interactively with travellers to handle the cold start problem. With the proposed method, a better online booking experience can be achieved for travellers, as they are presented with a more appropriate set of recommended options and so can make better travel decisions.
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