Solving Hanging Relevancy using Genetic Algorithm
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 I...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Published: |
Institute of Electrical and Electronics Engineers,
2012
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| Online Access: | http://hdl.handle.net/20.500.11937/26122 |
| _version_ | 1848751894157066240 |
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| author | Singh, Ashutosh Kumar Ravi, Kumar Goh, Kwang Leng Alex |
| author2 | John Wu (Contact) |
| author_facet | John Wu (Contact) Singh, Ashutosh Kumar Ravi, Kumar Goh, Kwang Leng Alex |
| author_sort | Singh, Ashutosh Kumar |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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). |
| first_indexed | 2025-11-14T07:59:58Z |
| format | Conference Paper |
| id | curtin-20.500.11937-26122 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:59:58Z |
| publishDate | 2012 |
| publisher | Institute of Electrical and Electronics Engineers, |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-261222017-09-13T15:24:45Z Solving Hanging Relevancy using Genetic Algorithm Singh, Ashutosh Kumar Ravi, Kumar Goh, Kwang Leng Alex John Wu (Contact) 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). 2012 Conference Paper http://hdl.handle.net/20.500.11937/26122 10.1109/URKE.2012.6319593 Institute of Electrical and Electronics Engineers, restricted |
| spellingShingle | Singh, Ashutosh Kumar Ravi, Kumar Goh, Kwang Leng Alex Solving Hanging Relevancy using Genetic Algorithm |
| title | Solving Hanging Relevancy using Genetic Algorithm |
| title_full | Solving Hanging Relevancy using Genetic Algorithm |
| title_fullStr | Solving Hanging Relevancy using Genetic Algorithm |
| title_full_unstemmed | Solving Hanging Relevancy using Genetic Algorithm |
| title_short | Solving Hanging Relevancy using Genetic Algorithm |
| title_sort | solving hanging relevancy using genetic algorithm |
| url | http://hdl.handle.net/20.500.11937/26122 |