A multimodality approach to predicting the popularity of sneakers

Mei Chen Yeh, Shao Ting Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We present a computational approach for predicting the popularity score of sneakers through the analysis of growing amount of online data. Sneakers are described in several aspects based on which a popularity prediction model is constructed. In particular, we utilize the multiple kernel learning technique with customized kernels to analyze multimodal data extracted from an online sneaker magazine. The construction of a prediction model from multiple facets is not trivial - the effectiveness of each feature depends on the way we compute and combine it with the others. We examine a few design choices and study how multimodal data should be utilized to achieve practical prediction.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages27-28
Number of pages2
ISBN (Electronic)9781479987443
DOIs
Publication statusPublished - 2015 Aug 20
Event2nd IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015 - Taipei, Taiwan
Duration: 2015 Jun 62015 Jun 8

Publication series

Name2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015

Other

Other2nd IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015
Country/TerritoryTaiwan
CityTaipei
Period2015/06/062015/06/08

Keywords

  • Computational modeling
  • Feature extraction
  • Image color analysis
  • Kernel
  • Predictive models
  • Shape
  • Training

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Instrumentation
  • Media Technology

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