Diversifying landmark image search results by learning interested views from community photos

Yuheng Ren, Mo Yu, Xin-Jing Wang, Lei Zhang, Wei-Ying Ma
2010 Proceedings of the 19th international conference on World wide web - WWW '10  
In this paper, we demonstrate a novel landmark photo search and browsing system, Agate, which ranks landmark image search results considering their relevance, diversity and quality. Agate learns from community photos the most interested aspects and related activities of a landmark, and generates adaptively a Table of Content (TOC) as a summary of the attractions to facilitate user browsing. Image search results are thus re-ranked with the TOC so as to ensure a quick overview of the attractions
more » ... f the landmarks. A novel non-parametric TOC generation and re-ranking algorithm, MoM-DPM Sets, is proposed as the key technology of Agate. Experimental results based on human evaluation show the effectiveness of our model and user preference for Agate. Keywords User interest modeling, set-based ranking, landmark image search.
doi:10.1145/1772690.1772904 dblp:conf/www/RenYWZM10 fatcat:ipdvts227ncuddjtua76cna7ce