COPE: interactive image retrieval using conversational recommendation

Bartoz Balcer, Martin Halvey, Stephen Brewster, Joemon Jose

Research output: Contribution to conferencePaperpeer-review


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
Publication statusPublished - 10 Sep 2012
Event26th Annual BCS Interaction Specialist Group Conference on People and Computers - Birmingham, United Kingdom
Duration: 10 Sep 2012 → …


Conference26th Annual BCS Interaction Specialist Group Conference on People and Computers
Abbreviated titleBCS-HCI 2012
Country/TerritoryUnited Kingdom
Period10/09/12 → …


  • multimedia retrieval
  • image retrieval
  • text based searching


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