Enhanced context-based query-to-concept mapping in social image retrieval

In a concept based image retrieval system, query-by-concept mapping is a new trend of query formulation using a set of predefined concepts in order to improve retrieval effectiveness. The key challenge is how to select the appropriate concepts since many of them will not directly be named in the query? In this paper, we propose a new approach for query to concept mapping based on the contextual correlations inter-concepts. Our idea is to explore Flickr resources in order to extract such correlations which will be presented as an inter-concepts graph. A random walk process will be performed over this graph to discover implicit concepts which are relevant to the query. Experimental studies are conducted on ImageCLEF 2011 Collection containing 250000 images, 99 concepts and 40 queries. The results show that our system runs reasonably and confirm the effectiveness of the proposed approach.