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Search Engine Spam Detection using an Integrated Hybrid Genetic Algorithm based Decision Tree

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
D. Saraswathi, A. Vijaya

D Saraswathi and A Vijaya. Article: Search Engine Spam Detection using an Integrated Hybrid Genetic Algorithm based Decision Tree. International Journal of Computer Applications 133(10):20-27, January 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

	author = {D. Saraswathi and A. Vijaya},
	title = {Article: Search Engine Spam Detection using an Integrated Hybrid Genetic Algorithm based Decision Tree},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {133},
	number = {10},
	pages = {20-27},
	month = {January},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}


Search Engine spam is a poison for the search engine. It is created by the search engine spammers for commercial benefits. It affects quality of search engine. Already there are many algorithms available for filtering the search engine spam. But the spammers are often changing the strategy for creating the search engine spam. So there is a need to detect it in efficient way. The proposed system detects the search engine spam using an integrated hybrid genetic algorithm based decision tree. The proposed system is compared with different criteria and is shown the best performance than other methods.


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Search Engine Spam, Decision Tree, Genetic Algorithm, Tabu Search, Spamdexing, Feature Selection, Metaheuristic Approach