effective browsing of web image search results
The rapid development of web image search engines has enabled users to search hundred million of images available on the Web. However, due to the unsatisfactory performance of current search technologies, people still need to spend much time in navigating through the large number of result pages to find images of their interest. In this paper, we analyze the user information needs for web image search results browsing and propose to employ a similarity-based organization to present the search results. A user study is carried out to compare our approach with a ranking-based list interface and a cluster-based interface. Experimental results show that similarity-based presentation can help users to explore image search results more naturally and efficiently
effect browse web imaging image search search developer user user performance technologies timing navigation paper information need organization present user studies interfaces experimentation help exploration multidimensional scaling web image retrieval attention model image browsing users user interface similarity ranking cluster