A Rose is a Roos is a Ruusu: Querying Translations for Web Image Search

We query Web Image search engines with words (e.g., spring) but need images that correspond to particular senses of the word (e.g., flexible coil). Querying with polysemous words often yields unsatisfactory results from engines such as Google Images. We build an image search engine, IDIOM, which improves the quality of returned images by focusing search on the desired sense. Our algorithm, instead of searching for the original query, searches for multiple, automatically chosen translations of the sense in several languages. Experimental results show that IDIOM outperforms Google Images and other competing algorithms returning 22% more relevant images.

• Type: Journal
• Year: 2009
• Where: ACL
• Authors: Janara Christensen, Mausam, Oren Etzioni
• Keywords: ACL 2009, Computational Linguistics, Google Images, Image Search, Images