Cross-modal information retrieval - A case study on Chinese wikipedia

From WikiPapers
Revision as of 12:37, November 7, 2014 by Nemo bis (Talk | contribs) (CSV import from another resource for wiki stuff; all data is PD-ineligible, abstracts quoted under quotation right. Skipping when title already exists. Sorry for authors and references to be postprocessed, please edit and create redirects.)

(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search

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).

[edit] Abstract

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.

[edit] References

This section requires expansion. Please, help!

Cited by

Probably, this publication is cited by others, but there are no articles available for them in WikiPapers.