Incorporating weight properties in detection of web spam
This paper focus on incorporating weight properties to enhance Web spam detection algorithms. Our proposed methodology adds this feature into Anti-TrustRank algorithm and call it weighted Anti-TrustRank algorithm to show the effectiveness of the weight properties using a new metric. Experiments are...
| 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/20.500.11937/31508 |
| _version_ | 1848753399492771840 |
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| author | Goh, Kwang Leng Alex Ravi, Kumar Singh, Ashutosh Kumar |
| author2 | John Wu (Contact) |
| author_facet | John Wu (Contact) Goh, Kwang Leng Alex Ravi, Kumar Singh, Ashutosh Kumar |
| author_sort | Goh, Kwang Leng Alex |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This paper focus on incorporating weight properties to enhance Web spam detection algorithms. Our proposed methodology adds this feature into Anti-TrustRank algorithm and call it weighted Anti-TrustRank algorithm to show the effectiveness of the weight properties using a new metric. Experiments are conducted on WEBSPAM-UK2006, a public Web spam dataset and have shown that weighted Anti-TrustRank significantly outperforms Anti-TrustRank algorithm up to 37.85%. |
| first_indexed | 2025-11-14T08:23:54Z |
| format | Conference Paper |
| id | curtin-20.500.11937-31508 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:23:54Z |
| publishDate | 2012 |
| publisher | Institute of Electrical and Electronics Engineers |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-315082017-09-13T15:20:30Z Incorporating weight properties in detection of web spam Goh, Kwang Leng Alex Ravi, Kumar Singh, Ashutosh Kumar John Wu (Contact) This paper focus on incorporating weight properties to enhance Web spam detection algorithms. Our proposed methodology adds this feature into Anti-TrustRank algorithm and call it weighted Anti-TrustRank algorithm to show the effectiveness of the weight properties using a new metric. Experiments are conducted on WEBSPAM-UK2006, a public Web spam dataset and have shown that weighted Anti-TrustRank significantly outperforms Anti-TrustRank algorithm up to 37.85%. 2012 Conference Paper http://hdl.handle.net/20.500.11937/31508 10.1109/URKE.2012.6319540 Institute of Electrical and Electronics Engineers restricted |
| spellingShingle | Goh, Kwang Leng Alex Ravi, Kumar Singh, Ashutosh Kumar Incorporating weight properties in detection of web spam |
| title | Incorporating weight properties in detection of web spam |
| title_full | Incorporating weight properties in detection of web spam |
| title_fullStr | Incorporating weight properties in detection of web spam |
| title_full_unstemmed | Incorporating weight properties in detection of web spam |
| title_short | Incorporating weight properties in detection of web spam |
| title_sort | incorporating weight properties in detection of web spam |
| url | http://hdl.handle.net/20.500.11937/31508 |