Abstract
The performance of ranking the retrieval results based on context and/or content information is usually limited because it depends heavily on the quality of the extracted information. Therefore, re-ranking approaches have been developed to improve the retrieval performance, but how to re-rank the retrieval results remains a challenge. In this paper, the inclusive and exclusive relationships between semantic concepts are utilized to re-rank the retrieval results. The inclusive relationship refers to the high co-occurrence relation between a target semantic concept and a reference semantic concept; while the exclusive relationship refers to the low or none co-occurrence relation. Moreover, multiple reference concepts provide more information from different aspects than only one reference concept does. Multiple Correspondence Analysis (MCA) is applied in this paper to capture the correlation in terms of the impact weights between attributes and the co-occurrence classes, and the average value of all the impact weights is utilized to re-rank the retrieved results for the target semantic concept. Experimental results on the MediaMill Challenge problem and the TRECVID 2011 video collections demonstrate that our proposed framework can enhance the retrieval results for a number of target semantic concepts.
