REGIMvid at ImageCLEF2012: Concept-based Query Refinement and Relevance-based Ranking Enhancement for Image Retrieval.

In this paper, we present our proposed approach that deals with two important steps in the retrieval process, which are query analysis and rele- vance-based ranking. First, query analysis takes into account two forms of que- ries: textual and visual which present the form of queries provided by ImageCLEF in the task " Visual concept detection, annotation, and retrieval us- ing Flickr photos ". The main idea in the query analysis process is to interpret the textual and visual queries and select the most appropriate concepts ac- cording to the query to concept mapping. Even the list of concepts is retained, we perform a query refinement process to improve the quality of the interpre- tation of the query. Second, we try to achieve a high-quality relevance-based result not only with choosing an adequate similarity measure but also with en- hancing obtained scores by elaborating a random walk with restart, which is performed over inter-images semantic similarity graph.