A Scalable Parallel HITS Algorithm for Page Ranking

Author

Bennett, Matthew ; Stone, Julie ; Zhang, Chaoyang

Author_Institution

Sch. of Comput., Univ. of Southern Mississippi, Hattiesburg, MS

Volume

1

fYear

2006

fDate

20-24 June 2006

Firstpage

437

Lastpage

442

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

Keywords

Internet; hypermedia; information retrieval; message passing; parallel algorithms; MPI; hyperlinked environment; hypertext induced topic search algorithm; information source; page ranking algorithm; scalable parallel HITS algorithm; shared memory supercomputer; Chaotic communication; Concurrent computing; Equations; Information retrieval; Internet; Performance analysis; Search engines; Supercomputers; Web pages; Web search;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Computational Sciences, 2006. IMSCCS '06. First International Multi-Symposiums on

Conference_Location

Hanzhou, Zhejiang

Print_ISBN

0-7695-2581-4

Type

conf

DOI

10.1109/IMSCCS.2006.22

Filename

4673586