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» Web page rank prediction with markov models
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WWW
2005
ACM
14 years 8 months ago
Adaptive page ranking with neural networks
Recent developments in the area of neural networks provided new models which are capable of processing general types of graph structures. Neural networks are well-known for their ...
Franco Scarselli, Sweah Liang Yong, Markus Hagenbu...
WWW
2004
ACM
14 years 8 months ago
Ranking the web frontier
The celebrated PageRank algorithm has proved to be a very effective paradigm for ranking results of web search algorithms. In this paper we refine this basic paradigm to take into...
Nadav Eiron, Kevin S. McCurley, John A. Tomlin
JMLR
2010
112views more  JMLR 2010»
13 years 2 months ago
Reduced-Rank Hidden Markov Models
Hsu et al. (2009) recently proposed an efficient, accurate spectral learning algorithm for Hidden Markov Models (HMMs). In this paper we relax their assumptions and prove a tighte...
Sajid M. Siddiqi, Byron Boots, Geoffrey J. Gordon
WWW
2010
ACM
14 years 2 months ago
Tracking the random surfer: empirically measured teleportation parameters in PageRank
PageRank computes the importance of each node in a directed graph under a random surfer model governed by a teleportation parameter. Commonly denoted alpha, this parameter models ...
David F. Gleich, Paul G. Constantine, Abraham D. F...
WAW
2004
Springer
150views Algorithms» more  WAW 2004»
14 years 1 months ago
Do Your Worst to Make the Best: Paradoxical Effects in PageRank Incremental Computations
d Abstract) Paolo Boldi† Massimo Santini‡ Sebastiano Vigna∗ Deciding which kind of visit accumulates high-quality pages more quickly is one of the most often debated issue i...
Paolo Boldi, Massimo Santini, Sebastiano Vigna