RT - Journal Article
T1 - IECA: Intelligent Effective Crawling Algorithm for Web Pages
JF - itrcjrn
YR - 2012
JO - itrcjrn
VO - 4
IS - 4
UR - http://ijict.itrc.ac.ir/article-1-171-en.html
SP - 33
EP - 42
K1 - search engines
K1 - Web crawling
K1 - Web graph
K1 - logarithmic distance
K1 - reinforcement learning
K1 - World Wide Web
AB - Obtaining important pages rapidly can be very useful when a crawler cannot visit the entire Webin a reasonable amount of time.Several Crawling algorithms such as Partial PageRank,Batch PageRank, OPIC, and FICA have been proposed, but they have high time complexity or low throughput. To overcome these problems, we propose a new crawling algorithm called IECA which is easy to implement with low time O(E*logV)and memory complexity O(V) -Vand Eare the number of nodes and edges in the Web graph, respectively. Unlike the mentioned algorithms, IECA traverses the Web graph only once and the importance of the Web pages is determined based on the logarithmic distance and weight of the incoming links. To evaluate IECA, we use threedifferent Web graphs such as the UK-2005, Web graph of university of California, Berkeley-2008, and Iran-2010. Experimental results show that our algorithm outperforms other crawling algorithms in discovering highly important pages.
LA eng
UL http://ijict.itrc.ac.ir/article-1-171-en.html
M3
ER -