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The Application of Similar Image Retrieval in Electronic Commerce

Traditional online shopping platform (OSP), which searches product information by keywords, faces three problems: indirect search mode, large search space, and inaccuracy in search results. For solving these problems, we discuss and research the application of similar image retrieval in electronic c...

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Detalles Bibliográficos
Autores principales: Hu, YuPing, Yin, Hua, Han, Dezhi, Yu, Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4032666/
https://www.ncbi.nlm.nih.gov/pubmed/24883411
http://dx.doi.org/10.1155/2014/579401
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author Hu, YuPing
Yin, Hua
Han, Dezhi
Yu, Fei
author_facet Hu, YuPing
Yin, Hua
Han, Dezhi
Yu, Fei
author_sort Hu, YuPing
collection PubMed
description Traditional online shopping platform (OSP), which searches product information by keywords, faces three problems: indirect search mode, large search space, and inaccuracy in search results. For solving these problems, we discuss and research the application of similar image retrieval in electronic commerce. Aiming at improving the network customers' experience and providing merchants with the accuracy of advertising, we design a reasonable and extensive electronic commerce application system, which includes three subsystems: image search display subsystem, image search subsystem, and product information collecting subsystem. This system can provide seamless connection between information platform and OSP, on which consumers can automatically and directly search similar images according to the pictures from information platform. At the same time, it can be used to provide accuracy of internet marketing for enterprises. The experiment shows the efficiency of constructing the system.
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spelling pubmed-40326662014-06-01 The Application of Similar Image Retrieval in Electronic Commerce Hu, YuPing Yin, Hua Han, Dezhi Yu, Fei ScientificWorldJournal Research Article Traditional online shopping platform (OSP), which searches product information by keywords, faces three problems: indirect search mode, large search space, and inaccuracy in search results. For solving these problems, we discuss and research the application of similar image retrieval in electronic commerce. Aiming at improving the network customers' experience and providing merchants with the accuracy of advertising, we design a reasonable and extensive electronic commerce application system, which includes three subsystems: image search display subsystem, image search subsystem, and product information collecting subsystem. This system can provide seamless connection between information platform and OSP, on which consumers can automatically and directly search similar images according to the pictures from information platform. At the same time, it can be used to provide accuracy of internet marketing for enterprises. The experiment shows the efficiency of constructing the system. Hindawi Publishing Corporation 2014 2014-04-22 /pmc/articles/PMC4032666/ /pubmed/24883411 http://dx.doi.org/10.1155/2014/579401 Text en Copyright © 2014 YuPing Hu et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Hu, YuPing
Yin, Hua
Han, Dezhi
Yu, Fei
The Application of Similar Image Retrieval in Electronic Commerce
title The Application of Similar Image Retrieval in Electronic Commerce
title_full The Application of Similar Image Retrieval in Electronic Commerce
title_fullStr The Application of Similar Image Retrieval in Electronic Commerce
title_full_unstemmed The Application of Similar Image Retrieval in Electronic Commerce
title_short The Application of Similar Image Retrieval in Electronic Commerce
title_sort application of similar image retrieval in electronic commerce
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4032666/
https://www.ncbi.nlm.nih.gov/pubmed/24883411
http://dx.doi.org/10.1155/2014/579401
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