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A Dual Layer Regression Model for Cross-border E-commerce Industry Sale and Hot Product Prediction

  • Wangda Luo
  • , Hang Su
  • , Yuhan Liu
  • , Ruifeng Xu*
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We introduce a novel regression model for time series forecasting in the cross-border e-commerce domain. In this paper, we present a new regression model for industry sale prediction (ISP) and hot product prediction (HPP) in the cross-border e-commerce domain. E-commerce products contain many attributes which may benefit to the final prediction performance. Based on this assumption, the proposed model employs a novel dual layer regression architecture to improve the generalization by capturing correlation between the historical data and future data, as well as enhancing the relationship of extracted features and target values. Besides, to verify the effectiveness of the proposed model, we establish two cross-border e-commerce datasets about imported lipsticks and shoes. The experimental results demonstrate that our proposed model achieves impressive results compared to a number of competitive baselines and the precision of hot product prediction reached 90%.

Original languageEnglish
Title of host publicationCognitive Computing – ICCC 2020 - 4th International Conference, Held as Part of the Services Conference Federation, SCF 2020, Proceedings
EditorsYujiu Yang, Lei Yu, Liang-Jie Zhang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages50-61
Number of pages12
ISBN (Print)9783030595845
DOIs
StatePublished - 2020
Externally publishedYes
Event4th International Conference on Cognitive Computing, ICCC 2020, held as part of Services Conference Federation, SCF 2020 - Honolulu, United States
Duration: 18 Sep 202020 Sep 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12408 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Conference on Cognitive Computing, ICCC 2020, held as part of Services Conference Federation, SCF 2020
Country/TerritoryUnited States
CityHonolulu
Period18/09/2020/09/20

Keywords

  • Dual layer architecture
  • Regression
  • Time series forecasting

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