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In this paper, we describe our experiments using Latent Dirichlet Allocation (LDA) to model images containing both perceptual features and words. To build a large-scale image tagging system, we distribute the computation of LDA parameters using MapReduce. Empirical study shows that our scalable LDA supports image annotation both effectively and efficiently.