Solving Hanging Relevancy Using Genetic Algorithm

被引：0

作者：

Singh, Ashutosh Kumar ^{[1
]}

Kumar, Ravi P. ^{[1
]}

Leng, Alex Goh Kwang ^{[1
]}

机构：

[1] Curtin Univ, Dept Elect & Comp Engn, Miri, Malaysia

来源：

2012 2ND INTERNATIONAL CONFERENCE ON UNCERTAINTY REASONING AND KNOWLEDGE ENGINEERING (URKE) | 2012年

关键词：

Hanging Pages; Hanging Relevancy; PageRank; Genetic Algorithm;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Continuous growth of hanging pages with Web makes a significant problem for ranking in the information retrieval. Exclusion of these pages in ranking calculation can give biased/inconsistent result. On the other hand inclusion of these pages will reduce the speed significantly. However 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 because of the complexity in computation and time. In our proposed method, we include the relevant hanging pages in the ranking. Relevancy or non-relevancy of hanging pages is achieved by application of Genetic Algorithm (GA).

引用

页码：9 / 12

页数：4

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