Cross-modal information retrieval - A case study on Chinese wikipedia
|Cross-modal information retrieval - A case study on Chinese wikipedia|
|Author(s)||Cong Y., Qin Z., Yu J., Wan T.|
|Published in||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Keyword(s)||Ch-Wikipedia, Character-based topics, Cross-modal information retrieval, Topic correlation model (TCM), Word-based topics (Extra: Ch-Wikipedia, Character-based topics, Correlation models, Cross-modal, Word-based topics, Semantics, Websites)|
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Cross-modal information retrieval - A case study on Chinese wikipedia is a 2012 conference paper written in English by Cong Y., Qin Z., Yu J., Wan T. and published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
Probability models have been used in cross-modalmultimedia information retrieval recently by building conjunctive models bridging the text and image components. Previous studies have shown that cross-modal information retrieval systemusing the topic correlation model (TCM) outperforms state-of-the-art models in English corpus. In this paper, we will focus on the Chinese language, which is different from western languages composed by alphabets. Words and characters will be chosen as the basic structural units of Chinese, respectively. We also set up a test database, named Ch-Wikipedia, in which documents with paired image and text are extracted fromChinese website ofWikipedia.We investigate the problems of retrieving texts (ranked by semantic closeness) given an image query, and vice versa. The capabilities of the TCM model is verified by experiments across the Ch-Wikipedia dataset.
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