Detecting Spam Blogs: A Machine Learning Approach
Abstract
Weblogs or sites are a significant better approach to distribute data, take part in conversations, and structure communities on the Internet. The Blogosphere has unfortunately been contaminated by a few assortments of spam-like substance. Blog web crawlers, for instance, are inundated by posts from splogs – bogus online journals with machine produced or commandeered content whose sole object is to have advertisements or raise the PageRank of target locales. We dis-cuss how SVM models dependent on nearby and connection based highlights can be utilized to distinguish splogs. We present an assessment of learned models and their utility to blog web indexes; frameworks that utilize methods contrast ing from those of traditional web crawlers.
How to cite this article:
Jain H, Thakur H. Detecting Spam Blogs: A Machine Learning Approach. J Adv Res Appl Arti Intel Neural Netw 2020; 4(2): 12-18.
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