Abstract
The literature review is a key component of academic research, which allows researchers to build upon each other's work. While modern search engines enable fast access to publications, there is a lack of support for filtering out the vast majority of papers that are irrelevant to the current research focus. We present PaperQuest, a visualization tool that supports efficient reading decisions, by only displaying the information useful at a given step of the review. We propose an algorithm to find and sort papers that are likely to be relevant to users, based on the papers they have already expressed interest in and the number of citations. The current implementation uses papers from the CHI, UIST, and VIS conferences, and citation counts from Google Scholar, but is easily extensible to other domains of the literature.