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Most of the current image indexing systems for retrieval view a database as a set of individual images. It limits the flexibility of the retrieval framework to conduct sophisticated cross-image analysis, resulting in higher memory consumption and sub-optimal retrieval accuracy. To conquer this issue, we propose cross indexing with grouplets, where the core idea is to view the database images as a...
Scalable and effective analysis of large text corpora remains a challenging problem as our ability to collect textual data continues to increase at an exponential rate. To help users make sense of large text corpora, we present a novel visual analytics system, Parallel-Topics, which integrates a state-of-the-art probabilistic topic model Latent Dirichlet Allocation (LDA) with interactive visualization...
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