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• W2504820066 abstract "Abstract Traditional feature-based or text processing techniques tend to assign the same annotation to all the images in the same cluster without considering the latent semantic anecdotes of each image. In this research, we propose the Chinese lexical chain processing method which is a bottom-up concatenating process based on the intensity and the degree of a lexical chain (LC) to extract the most meaningful LCs as anecdotes from a string. It requires minimum computation that allows sharing characters/words and facilitating their use at fine granularities without prohibitive cost. In the experiment, this method achieves a precision rate of 84.6%, and gains acceptance from expert rating and user rating of 84% and 76.6%, respectively. In performance testing, it only takes 0.007 s to process each image in a collection of 18,000 testing data set." @default.
• W2504820066 created "2016-08-23" @default.
• W2504820066 creator A5043135511 @default.
• W2504820066 date "2015-01-01" @default.
• W2504820066 modified "2023-09-27" @default.
• W2504820066 title "Anecdotes extraction from webpage context as image annotation" @default.
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• W2504820066 doi "https://doi.org/10.1016/b978-0-12-802045-6.00022-3" @default.
• W2504820066 hasPublicationYear "2015" @default.
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