An online-to-offline service recommendation method based on two-layer knowledge networks

发表期刊：

Information Sciences

论文层级：

人大A，中科院一区，JCR一区

论文作者：

Yuchen Pan, Lu Xu, Desheng Dash Wu and David L. Olson

论文摘要：

This paper introduces a novel method aimed at enhancing online-to-offline (O2O) services recommendations by utilizing two-layer knowledge networks. The primary objective of this method is to assist consumers in efficiently navigating the myriad of options available when choosing O2O services. Using co-occurrence relationships, we construct a two-layer knowledge network system, comprising a service knowledge network based on service usage information as the first layer and a consumer knowledge network, built on "co-used" behaviors as the second layer. The former is established upon service use data, while the latter is founded on “co-used” behaviors among consumers. The features and information of these two knowledge networks can complement each other to produce precise and effective recommendations. Empirical findings gained from our experiments demonstrate that: (1) the proposed recommendation method outperforms widely-used and state-of-the-art recommendation methods; (2) both the service knowledge network and consumer knowledge network play an equally significant role in O2O service recommendations; (3) the location of O2O services is an essential factor in consumers’ choices for services. Notably, this research also identifies the optimal parameter settings for the proposed recommendation method.