Visual Re-Ranking for Multi-Aspect Information Retrieval

We present visual re-ranking, an interactive visualization technique for multi-aspect information retrieval. In multi-aspect search, the information need of the user consists of more than one aspect or query simultaneously. While visualization and interactive search user interface techniques for improving user interpretation of search results have been proposed, the current research lacks understanding on how useful these are for the user: whether they lead to quantifiable benefits in perceiving the result space and allow faster, and more precise retrieval. Our technique visualizes relevance and document density on a two-dimensional map with respect to the query phrases. Pointing to a location on the map specifies a weight distribution of the relevance to each of the query phrases, according to which search results are re-ranked. User experiments compared our technique to a uni-dimensional search interface with typed query and ranked result list, in perception and retrieval tasks. Visual reranking yielded improved accuracy in perception, higher precision in retrieval and overall faster task execution. Our findings demonstrate the utility of visual re-ranking, and can help designing search user interfaces that support multi-aspect search.