Improving Web search using image snippets

  • Authors:

  • Xiao-Bing Xue;Zhi-Hua Zhou;Zhongfei (Mark) Zhang

  • Affiliations:

  • Nanjing University, Nanjing, China;Nanjing University, Nanjing, China;SUNY at Binghamton, Binghamton, NY

  • Venue:
  • ACM Transactions on Internet Technology (TOIT)
  • Year:
  • 2008

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Abstract

The Web has become the largest information repository in the world; thus, effectively and efficiently searching the Web becomes a key challenge. Interactive Web search divides the search process into several rounds, and for each round the search engine interacts with the user for more knowledge of the user's information requirement. Previous research mainly uses the text information on Web pages, while little attention is paid to other modalities. This article shows that Web search performance can be significantly improved if imagery is considered in interactive Web search. Compared with text, imagery has its own advantage: the time for “reading” an image is as little as that for reading one or two words, while the information brought by an image is as much as that conveyed by a whole passage of text. In order to exploit the advantages of imagery, a novel interactive Web search framework is proposed, where image snippets are first extracted from Web pages and then provided, along with the text snippets, to the user for result presentation and relevance feedback, as well as being presented alone to the user for image suggestion. User studies show that it is more convenient for the user to identify the Web pages he or she expects and to reformulate the initial query. Further experiments demonstrate the promise of introducing multimodal techniques into the proposed interactive Web search framework.