Personalized PageRank, related to random walks with restarts and conductance in resistive networks, is a frequent search paradigm for graph-structured databases. While efficient ba...
The paper is concerned with learning to rank, which is to construct a model or a function for ranking objects. Learning to rank is useful for document retrieval, collaborative fil...
Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, Han...
In the paper we show that diagnostic classes in cancer gene expression data sets, which most often include thousands of features (genes), may be effectively separated with simple ...
Gregor Leban, Minca Mramor, Ivan Bratko, Blaz Zupa...
— The main objetive of this paper is to improve the current status of learning object search. First, the current situation is analyzed and a theretical solution, based on relevan...
This paper focuses on using hyperlinks in the ranking of web search results. We give a brief overview of the vast body of work in the area; we provide a quantitative comparison of ...