A Scalable Parallel HITS Algorithm For Page Ranking
Document Type
Conference Proceeding
Publication Date
12-22-2006
School
Computing Sciences and Computer Engineering
Abstract
The Hypertext Induced Topic Search (HITS) algorithm is a method of ranking authority of information sources in a hyperlinked environment. HITS uses only topological properties of the hyperlinked network to determine rankings. We present an efficient and scalable implementation of the HITS algorithm that uses MPI as an underlying means of communication. We then analyze the performance on a shared memory supercomputer, and use our results to verify the optimal number of processors needed to rank a large number of pages for the link structure of the total University of Southern Mississippi (usm.edu domain) web sites. © 2006 IEEE.
Publication Title
First International Multi- Symposiums on Computer and Computational Sciences, IMSCCS'06
First Page
437
Last Page
442
Recommended Citation
Bennett, M.,
Stone, J.,
Zhang, C.
(2006). A Scalable Parallel HITS Algorithm For Page Ranking. First International Multi- Symposiums on Computer and Computational Sciences, IMSCCS'06, 437-442.
Available at: https://aquila.usm.edu/fac_pubs/17946