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When Amazon Meets Google: Product Visualization by Exploring Multiple Web Sources

Published:01 July 2013Publication History
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Abstract

Product visualization is able to help users easily get knowledge about the visual appearance of a product. It is useful in many application and commercialization scenarios. However, the existing product image search on e-commerce Web sites or general search engines usually get insufficient search results or return images that are redundant and not relevant enough. In this article, we present a novel product visualization approach that automatically collects a set of diverse and relevant product images by exploring multiple Web sources. Our approach simultaneously leverages Amazon and Google image search engines, which represent domain-specific knowledge resource and general Web information collection, respectively. We propose a conditional clustering approach that is formulated as an affinity propagation problem regarding the Amazon examples as information prior. The ranking information of Google image search results is also explored. In this way, a set of exemplars can be found from the Google search results and they are provided together with the Amazon example images for product visualization. Experiments demonstrate the feasibility and effectiveness of our approach.

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    • Published in

      cover image ACM Transactions on Internet Technology
      ACM Transactions on Internet Technology  Volume 12, Issue 4
      July 2013
      64 pages
      ISSN:1533-5399
      EISSN:1557-6051
      DOI:10.1145/2499926
      Issue’s Table of Contents

      Copyright © 2013 ACM

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 1 July 2013
      • Accepted: 1 April 2013
      • Revised: 1 October 2012
      • Received: 1 April 2012
      Published in toit Volume 12, Issue 4

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