TaxoVec: Taxonomy Based Representation for Web User Profiling
Qinpei Zhao, Xiongbaixue Yan, Yinjia Zhang, Weixiong Rao, Jiangfeng Li, Chao Mi, Jessie Chen · 2021
Web users provide rich multi-modal and heterogeneous data. Taking use of the data for extracting the representation of web users is a vital prerequisite of further profiling tasks. In this paper, we study the web user profiling based on the user-entity interaction data integrating the taxonomy information of the entity. To overcome the challenges of the representation of a web user and the distance definition of two web users, we introduce TaxoVec, an interpretable method to represent a user’s interaction history by vectors with the help of the entities’ category information. The TaxoVec is employed in clustering-based web user profiling on their transaction data and geographical data, which provide the information on their interests and activity area. Experiments show that the TaxoVec performs well on representing characteristics of web users.