Pivotbrowser: a tag-space image searching prototype

We propose a novel iterative searching and refining prototype for tagged images. This prototype, named PivotBrowser, captures semantically similar tag sets in a structure called pivot. By constructing a pivot for a textual query, PivotBrowser first selects candidate images possibly relevant to the query. The tags contained in these candidate images are then selected in terms of their tag relevances to the pivot. The shortlisted tags are clustered and one of the tag clusters is used to select the results from the candidate images. Ranking of the images in each partition is based on their relevance to the tag cluster. With the guidance of the tag clusters presented, a user is able to perform searching and iterative query refinement. Categories and Subject Descriptors: H.4 [Information Systems Applications]: Miscellaneous General Terms: Algorithms, Design

• Type: Conference
• Year: 2008
• Where: WWW
• Authors: Xiaoyan Li, Lidan Shou, Gang Chen, Xiaolong Zhang, Tianlei Hu, Jinxiang Dong
• Keywords: Internet Technology, Iterative Query Refinement, Similar Tag Sets, Tag Clusters, WWW 2008