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We present correspondence with category Latent Dirichlet Allocation (corr-c-LDA), a novel probabilistic topic model for the task of image and video annotation. The heart of our annotation model lies in introducing the class label information and assuming the dependence relationships between class label and image feature, as well as class label and annotation words. Instead of modeling the image and...
Considering of the features' distribution but not just the counts of features' appearances in sequence makes exponential language models more powerful to capture the global language phenomena. This paper constructs an exponential language model with binary variables' distributions of features, and uses minimum sample risk training method to train model by utilizing more features and adjusting their...
This paper presents an exponential language model (ELM) for modeling and managing knowledge elements. The model has been developed based on minimum sample risk (MSR) algorithm, which is a discriminative training method. ELM uses features to capture global, domain, or sentential language phenomena that is composed of name entities, part of speech strings, personal usage words, positions of words, sentence...
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