Lumping with acceleration for PageRank computation

• Type: Article in International Conference Proceedings Book
• Date: 2014

Authors

Mendes, IR (Author) Other; vasconcelos, pb (Author) FEP

Conference proceedings International

Title: 2014 14TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND ITS APPLICATIONS (ICCSA)

Pages: 221-224

14th International Conference on Computational Science and Its Applications (ICCSA)

Guimaraes, PORTUGAL, JUN 30-JUL 03, 2014

Indexing

ISI Web of Knowledge - 3 Citations

Scopus - 3 Citations

Other information

Authenticus ID: P-00A-65V

DOI: 10.1109/iccsa.2014.50

Abstract (EN): Web information retrieval is extremely challenging due to the huge number of web pages. The success of a search engine relies on its capacity to deploy fast, accurately and in order, a set of results satisfying a particular query. To determine the order of importance in which to display web pages after a query, Google's search engine computes the PageRank vector, the left principal eigenvector of a web matrix that is related to the hyperlink structure of the web, the Google matrix. From a computational mathematics viewpoint the most important part of the Google search engine is the PageRank computation, mainly the numerical linear algebra behind as well as the use of adequate techniques to accelerate its computation. In this work we intend to contribute for the acceleration of the PageRank computation by combining reordered techniques with extrapolation. We propose a novel algorithm by considering standard extrapolation within the lumping method. Results show the benefits from our proposal.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4