BrowseRank algorithm and its modifications are based on analyzing users' browsing trails. Our paper proposes a new method for computing page importance using a more realistic and effective search-aware model of user browsing behavior than the one used in BrowseRank.
In this paper we propose a framework for obtaining quasi-dense Euclidean structure reconstruction by means of guided quasi-dense point tracking in image sequences. We use a stratified algorithm that establishes most reliable sparse point correspondences first then robustly estimates multiview geometry and finally propagates sparse point features to… (More)
In the last years, a lot of attention was attracted by the problem of page authority computation based on user browsing behavior. However, the proposed methods have a number of limitations. In particular, they run on a single snapshot of a user browsing graph ignoring substantially dynamic nature of user browsing activity, which makes such methods recency… (More)