1) The document proposes personalized retrieval methods in social bookmarking systems to improve users' ability to refind bookmarks. 2) It describes a bookmark refinding scenario where a user filters their bookmark list using tags to find a target bookmark, and analyzes how many filters it takes users to refind bookmarks. 3) The authors develop a personalized ordering metric based on individual users' access histories to rank bookmarks higher that they are more likely to want to refind, improving the position of target bookmarks in search results and reducing the number of filters needed to find them.