In many example-based information retrieval tasks, example query actually contains multiple sub-queries. For example, in 3D object retrieval, the query is an object described by multiple views. In content-based video retrieval, the query is a video clip that contains multiple frames. Without prior knowledge, the most intuitive approach is to treat the sub-queries equally without difference. In this paper, we propose a k-partite graph reinforcement approach to fuse these sub-queries based on the to-be-retrieved database. The approach first collects the top retrieved results. These results are regarded as pseudo-relevant samples and then a k-partite graph reinforcement is performed on these samples and the query. In the reinforcement process, the weights of the sub-queries are updated by an iterative process. We present experiments on 3D object retrieval and content-based video clip retrieval, and the results demonstrate that our method effectively boosts retrieval performance
Multimedia, information retrieval, k-Partite, graph reinforcement, 3D object retrieval, Video retrieval
Databases and Information Systems
Data Management and Analytics
GAO, Yue; WANG, Meng; Ji, Rongrong; ZHA, Zheng-Jun; and SHEN, Jialie.
k-Partite Graph Reinforcement and its Application in Multimedia Information Retrieval. (2012). Information Sciences. 194, 224-239. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1497
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