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Luis A. Leiva, Mauricio Villegas, Roberto Paredes. Query Refinement Suggestion in Multimodal Interactive Image Retrieval. Proceedings of the 13th International Conference on Multimodal Interaction (ICMI), 2011. pp. 311-314.

In the literature, it has been shown that relevance feedback is a good strategy for the system to interact with the user and provide better results in a content-based image retrieval (CBIR) system. On the other hand, there are many retrieval systems which suggest a refinement of the query as the user types, which effectively helps the user to obtain better results with less effort. Based on these observations, in this work we propose to add a suggested query refinement as a complement in an image retrieval system with relevance feedback. Taking advantage of the nature of the relevance feedback, in which the user selects relevant images, the query suggestions are derived using this relevance information. From the results of an evaluation performed, it can be said that this type of query suggestion is a very good enhancement to the relevance feedback scheme, and can potentially lead to better retrieval performance and less effort from the user.