TUR: Utilizing Temporal Information to Make Unexpected E-Commerce Recommendations

Yongxin Ni, Ningxia Wang*, Li Chen, Rui Chen, Lei Li

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review


Unexpectedness recommendations are getting more attention as a solution to the over-specialization of traditional accuracy-oriented recommender systems. However, most of the existing works make limited use of available interaction information to compute distance and neglect the fact that varying time intervals for recommendations would lead to different perceptions of unexpectedness from users. In this work, we propose a novel Temporal Unexpected Recommendation (TUR) approach to improve e-commerce recommendations’ unexpectedness. Specifically, we consider the complementarity of both implicit and explicit distances, modeling unexpectedness from the latent space (i.e., embedding vectors) and the side information (i.e., item taxonomy) respectively. Meanwhile, we import a module based on the time-aware GRU to leverage the impact of timeliness on recommendation unexpectedness. Experiments on a large-scale e-commerce dataset containing real users’ feedback show that TUR significantly outperforms the baselines in enhancing unexpectedness while maintaining a comparable accuracy level.

Original languageEnglish
Title of host publicationWeb Information Systems Engineering – WISE 2022
Subtitle of host publication23rd International Conference, Biarritz, France, November 1–3, 2022, Proceedings
EditorsRichard Chbeir, Helen Huang, Fabrizio Silvestri, Yannis Manolopoulos, Yanchun Zhang
PublisherSpringer Cham
Number of pages11
ISBN (Electronic)9783031208911
ISBN (Print)9783031208904
Publication statusPublished - 6 Nov 2022
Event23rd International Conference on Web Information Systems Engineering, WISE 2022 - Biarritz, France
Duration: 1 Nov 20223 Nov 2022

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameWISE: International Conference on Web Information Systems Engineering


Conference23rd International Conference on Web Information Systems Engineering, WISE 2022
Internet address

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • E-commerce
  • Recommender systems
  • Timeliness
  • Unexpectedness


Dive into the research topics of 'TUR: Utilizing Temporal Information to Make Unexpected E-Commerce Recommendations'. Together they form a unique fingerprint.

Cite this