Predicting E-commerce Item Sales With Web Environment Temporal Background

Video in TIB AV-Portal: Predicting E-commerce Item Sales With Web Environment Temporal Background

Formal Metadata

Title
Predicting E-commerce Item Sales With Web Environment Temporal Background
Title of Series
Author
License
CC Attribution - NonCommercial 4.0 International:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
Identifiers
Publisher
Release Date
2021
Language
English

Content Metadata

Subject Area
Abstract
In this paper, we study the effect of Web environment temporal background in pre-dicting e-commerce item sales, especially those in temporary sales. Temporary sales nowadaysare a popular strategy for quickly clearing inventories. For traditional recommender systems,predicting the sales of an item is done based on its past purchase records. For temporarysales items, however, such records are not available. In order to make recommendation forsuch items, contextual information, such as product descriptions, is usually used. We investi-gate whether temporal background in the Web environment can be additional useful contextualinformation in recommender systems. It is assumed that items consistent with the temporalbackground would have higher demands. We propose a method for representing the temporalbackground using word embeddings of e-commerce activities and social media data, and eval-uate their effect on sales prediction. Through empirical analysis with real-world data, we foundthat temporal background does have positive effects for sales prediction. The findings in thispaper can be conveniently incorporated into future recommender system designs.
Keywords e-commerce recommender social media

Related Material

Video is accompanying material for the following resource
Feedback