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Sentiment expression in microblog posts often reflects user’s specific individuality due to different language habit, personal character, opinion bias and so on. Existing sentiment classification algorithms largely ignore such latent personal distinctions among different microblog users. Meanwhile, sentiment data of microblogs are sparse for individual(More)
Extensive experiments have validated the effectiveness of the corpus-based method for classifying the word’s sentiment polarity. However, no work is done for comparing different corpora in the polarity classification task. Nowadays, Twitter has aggregated huge amount of data that are full of people’s sentiments. In this paper, we empirically evaluate the(More)
In content-based image retrieval, understanding the user’s needs in the process of retrieval is a challenging task. Relevance feedback (RF) has been proven to be an effective method for integrating the user’s knowledge into the retrieval process to eliminate the semantic gap between the high level semantic concept and the low level features(More)