Solving hanging relevancy using genetic algorithm

Singh, Ashutosh Kumar; Ravi, Kumar; Leng, Alex Goh Kwang

doi:10.1109/urke.2012.6319593

Cited by 1 publication

(1 citation statement)

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“…Another method, by Ipsen and Selee (2007), also separates the hanging pages from the nonhanging ones and computes the PageRank. There were also methods proposed by Bianchini, Gori, and Scarselli (2005) and Singh, Kumar, and Goh (2010, 2012 to include hanging pages in the ranking process. All these methods either leave the hanging pages or include the hanging pages in the rank computation.…”

Section: Related Workmentioning

confidence: 99%

Efficient Methodologies to Determine the Relevancy of Hanging Pages Using Stability Analysis

Kumar

Leng

Singh

et al. 2016

Cybernetics and Systems

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This article presents an algorithm to determine the relevancy of hanging pages in the link-structure-based ranking algorithms. Recently, hanging pages have become major obstacles in web information retrieval (IR). As an increasing number of meaningful hanging pages appear on the Web, their relevancy has to be determined according to the query term in order to make the search engine result pages fair and relevant. Exclusion of these pages in ranking calculation can give biased/inconsistent results, but inclusion of these pages will reduce the speed significantly. Most of the IR ranking algorithms exclude the hanging pages. But there are relevant and important hanging pages on the Web, and they cannot be ignored. In our proposed method, we use anchor text to determine the hanging relevancy, and we use stability analysis to show that rank results are consistent before and after altering the link structure.

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Section: Related Workmentioning

confidence: 99%