Link-based web spam detection using weight properties
Link spam is created with the intention of boosting one target’s rank in exchange of business profit. This unethical way of deceiving Web search engines is known as Web spam. Since then many anti-link spam detection techniques have constantly being proposed. Web spam detection is a crucial task due...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
Springer New York LLC
2014
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| Online Access: | http://hdl.handle.net/20.500.11937/28483 |
| _version_ | 1848752549507629056 |
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| author | Goh, K. Patchmuthu, Ravi Kumar Singh, Ashutosh Kumar |
| author_facet | Goh, K. Patchmuthu, Ravi Kumar Singh, Ashutosh Kumar |
| author_sort | Goh, K. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Link spam is created with the intention of boosting one target’s rank in exchange of business profit. This unethical way of deceiving Web search engines is known as Web spam. Since then many anti-link spam detection techniques have constantly being proposed. Web spam detection is a crucial task due to its devastation towards Web search engines and global cost of billion dollars annually. In this paper, we proposed a novel technique by incorporating weight properties to enhance the Web spam detection algorithms. Weight properties can be defined as the influences of one Web node towards another Web node. We modified existing Web spam detection algorithms with our novel technique to evaluate the performances on a large public Web spam dataset – WEBSPAM-UK2007. The overall performance have shown that the modified algorithms outperform the benchmark algorithms up to 30.5 % improvement at host level and 6.11 % improvement at page level. |
| first_indexed | 2025-11-14T08:10:23Z |
| format | Journal Article |
| id | curtin-20.500.11937-28483 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:10:23Z |
| publishDate | 2014 |
| publisher | Springer New York LLC |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-284832017-09-13T15:19:35Z Link-based web spam detection using weight properties Goh, K. Patchmuthu, Ravi Kumar Singh, Ashutosh Kumar Link spam is created with the intention of boosting one target’s rank in exchange of business profit. This unethical way of deceiving Web search engines is known as Web spam. Since then many anti-link spam detection techniques have constantly being proposed. Web spam detection is a crucial task due to its devastation towards Web search engines and global cost of billion dollars annually. In this paper, we proposed a novel technique by incorporating weight properties to enhance the Web spam detection algorithms. Weight properties can be defined as the influences of one Web node towards another Web node. We modified existing Web spam detection algorithms with our novel technique to evaluate the performances on a large public Web spam dataset – WEBSPAM-UK2007. The overall performance have shown that the modified algorithms outperform the benchmark algorithms up to 30.5 % improvement at host level and 6.11 % improvement at page level. 2014 Journal Article http://hdl.handle.net/20.500.11937/28483 10.1007/s10844-014-0310-y Springer New York LLC restricted |
| spellingShingle | Goh, K. Patchmuthu, Ravi Kumar Singh, Ashutosh Kumar Link-based web spam detection using weight properties |
| title | Link-based web spam detection using weight properties |
| title_full | Link-based web spam detection using weight properties |
| title_fullStr | Link-based web spam detection using weight properties |
| title_full_unstemmed | Link-based web spam detection using weight properties |
| title_short | Link-based web spam detection using weight properties |
| title_sort | link-based web spam detection using weight properties |
| url | http://hdl.handle.net/20.500.11937/28483 |