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To better understand the content of multimedia, a lot of research efforts have been made on how to learn from multi-modal feature. In this paper, it is studied from a graph point of view: each kind of feature from one modality is represented as one independent graph; and the learning task is formulated as inferring from the constraints in every graph as well as supervision information (if available). For semi-supervised learning, two different fusion schemes, namely linear form and sequentialdoi:10.1145/1101149.1101337 dblp:conf/mm/TongHLZM05 fatcat:ux2tzibo6nbfrhr3pca2hxme6m