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Effective browsing of web image search results

  • Hao Liu
  • , Xing Xie
  • , Xiaoou Tang
  • , Zhi-Wei Li
  • , Wei-Ying Ma

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

The rapid development of web image search engines has enabled users to search hundred million of images available on the Web. However, due to the unsatisfactory performance of current search technologies, people still need to spend much time in navigating through the large number of result pages to find images of their interest. In this paper, we analyze the user information needs for web image search results browsing and propose to employ a similarity-based organization to present the search results. A user study is carried out to compare our approach with a ranking-based list interface and a cluster-based interface. Experimental results show that similarity-based presentation can help users to explore image search results more naturally and efficiently. Copyright 2004 ACM.
Original languageEnglish
Title of host publicationMIR'04 - Proceedings of the 6th ACM SIGMM International Workshop on Multimedia Information Retrieval
Pages84-90
DOIs
Publication statusPublished - 2004
Externally publishedYes
EventMIR'04 - Proceedings of the 6th ACM SIGMM International Workshop on Multimedia Information Retrieval - New York, NY, United States
Duration: 15 Oct 2004 → 16 Oct 2004

Publication series

NameMIR'04 - Proceedings of the 6th ACM SIGMM International Workshop on Multimedia Information Retrieval

Conference

ConferenceMIR'04 - Proceedings of the 6th ACM SIGMM International Workshop on Multimedia Information Retrieval
PlaceUnited States
CityNew York, NY
Period15/10/04 → 16/10/04

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

  • Attention model
  • Image browsing
  • Multidimensional scaling
  • User interface
  • Web image retrieval

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