Collaborative Knowledge Semantic Graph Image Search
In this paper, we propose a Collaborative Knowledge Semantic Graphs Image Search (CKSGIS) system. It provides a novel way to conduct image search by utilizing the collaborative nature in Wikipedia and by performing network analysis to form semantic graphs for search-term expansion. The collaborative article editing process used by Wikipedias contributors is formalized as bipartite graphs that are folded into networks between terms. When a user types in a search term, CKSGIS automatically retrieves an interactive semantic graph of related terms that allow users to easily find related images not limited to a specific search term. Interactive semantic graph then serve as an interface to retrieve images through existing commercial search engines. This method significantly saves users time by avoiding multiple search keywords that are usually required in generic search engines. It benefits both na(I)ve users who do not possess a large vocabulary and professionals who look for images on a regular basis. In our experiments, 85％ of the participants favored CKSGIS system rather than commercial search engines.
Social Network Keyword Expansion Re-ranking
Jyh-Ren Shieh Yang-Ting Yeh Chih-Hung Lin Ching-Yung Lin Ja-Ling Wu
Dept. Of Computer Science and Information Engineering National Taiwan University Taipei 106, Taiwan IBM T. J. Watson Research Center Hawthorne, NY 10532,USA
国际会议
第十七届国际万维网大会(the 17th International World Wide Web Conference)(WWW08)
北京
英文
2008-04-21（万方平台首次上网日期，不代表论文的发表时间）