In this paper, we analyze the efficiency of Monte Carlo methods for incremental computation of PageRank, personalized PageRank, and similar random walk based methods (with focus o...
We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...
This paper presents a stochastic graph based method for recommending or selecting a small subset of blogs that best represents a much larger set. within a certain topic. Each blog...
Ahmed Hassan, Dragomir R. Radev, Junghoo Cho, Amru...
The quantum analog of a constraint satisfaction problem is a sum of local Hamiltonians - each (term of the) Hamiltonian specifies a local constraint whose violation contributes to...
Dorit Aharonov, Itai Arad, Zeph Landau, Umesh V. V...
We propose a General Markov Framework for computing page importance. Under the framework, a Markov Skeleton Process is used to model the random walk conducted by the web surfer on...
Bin Gao, Tie-Yan Liu, Zhiming Ma, Taifeng Wang, Ha...