COPE: interactive image retrieval using conversational recommendation

Bartoz Balcer, Martin Halvey, Stephen A. Brewster, Joemon M. Jose

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


    Most multimedia retrieval services e.g. YouTube, Flickr, Google etc. rely on users searching using textual queries or examples. However, this solution is inadequate when there is no text, very little text, the text is in a foreign language or the user cannot form textual a query. In order to overcome these shortcomings we have developed an image retrieval system called COPE (COnversational Picture Exploration) that can use a number of different preference feedback mechanisms, inspired by conversational recommendation paradigms, for image retrieval. In COPE users are presented with a small number of search results and simply have to express whether these results match their information need. We examine the suitability of a number of feedback approaches for semiautomatic and interactive image retrieval. For interactive retrieval we compared our preference based approaches to text based search (where we consider text to be an upper bound), our results indicate that users prefer preference based search to text based search and in some cases our approaches can outperform text based search.
    Original languageEnglish
    Title of host publicationProceedings of the HCI 2012 The 26th BCS Conference on Human Computer Interaction
    PublisherBCS, The Chartered Institute for IT
    Number of pages10
    Publication statusPublished - 12 Sep 2012


    • multimedia retrieval services
    • COPE
    • image retrieval system
    • browsing
    • social media


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