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Machine Learning for Web Spam Detection by suryarastogi01 is a document available to read on EtoBox.

What is Machine Learning for Web Spam Detection about?

This paper provides a comprehensive comparison of machine learning algorithms for web spam classification, focusing on their performance using two public datasets, WEBSPAM-UK2006 and WEBSPAM-UK2007. It evaluates various classifiers, including Random Forest and AdaBoost, and highlights that Random Forest with AdaBoost variations achieved the highest performance metrics. The study aims to enhance spam detection through the application of ensemble meta-learning algorithms and standardized evaluation metrics.

Author

suryarastogi01

Language

EN