DocumentCode :
3503118
Title :
Parallel adaptive technique for computing PageRank
Author :
Rungsawang, Arnon ; Manaskasemsak, Bundit
Author_Institution :
Dept. of Comput. Eng., Kasetsart Univ., Bangkok, Thailand
fYear :
2006
fDate :
15-17 Feb. 2006
Abstract :
Re-ranking the search results using PageRank is a well-known technique used in modern search engines. Running an iterative algorithm like PageRank on a large Web graph consumes both much computing resource and time. This paper therefore proposes a parallel adaptive technique for computing PageRank using the PC cluster. Following the study of the Stanford WebBase group on convergence patterns of PageRank scores of pages using the conventional PageRank algorithm, PageRank scores of most pages converge more quickly than the remainder, we then devise our parallel adaptive algorithm to reiterate the computation for pages whose PageRank scores are still not converged. From experiments using a synthesized Web graph of 28 million pages and around 227 million hyperlinks, we obtain the acceleration rate up to 6-8 times using 32 PC processors.
Keywords :
Internet; information retrieval; iterative methods; parallel algorithms; search engines; PC cluster; PageRank algorithm; Web graph; iterative algorithm; parallel adaptive technique; search engines; Acceleration; Adaptive algorithm; Clustering algorithms; Concurrent computing; Convergence; Iterative algorithms; Knowledge engineering; Search engines; Web pages; Web search;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel, Distributed, and Network-Based Processing, 2006. PDP 2006. 14th Euromicro International Conference on
ISSN :
1066-6192
Print_ISBN :
0-7695-2513-X
Type :
conf
DOI :
10.1109/PDP.2006.55
Filename :
1613249
Link To Document :
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