Improving convergence performance of pagerank computation based on step-length calculation approach

Authors:
Kazumi Saito;Ryohei Nakano
Affiliations:
NTT Communication Science Laboratories, Soraku, Kyoto, Japan;Nagoya Institute of Technology, Nagoya, Japan
Venue:
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Year:
2006

Citing 3
Cited 0

The anatomy of a large-scale hypertextual Web search engine

WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment

Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Neural Networks for Pattern Recognition

Neural Networks for Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

We address the task of improving convergence performance of PageRank computation. Based on a step-length calculation approach, we derive three methods, which respectively calculates its step-length so as to make the successive search directions orthogonal (orthogonal direction), minimize the error at the next iteration (minimum error) and make the successive search directions conjugate (conjugate direction). In our experiments using a real Web network, we show that the minimum error method is promising for this task.