Incorporating weight properties in detection of web spam
MetadataShow full item record
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%.
Showing items related by title, author, creator and subject.
Goh, Kwang Leng (2013)Web spamming has tremendously subverted the ranking mechanism of information retrieval in Web search engines. It manipulates data source maliciously either by contents or links with the intention of contributing negative ...
Goh, K.; Patchmuthu, Ravi Kumar; Singh, Ashutosh Kumar (2014)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 ...
Kumar, R.; Singh, Ashutosh Kumar (2010)Problem statement: A study on hyperlink analysis and the algorithms used for link analysis in the Web Information retrieval was done. Approach: This research was initiated because of the dependability of search engines ...