Content - Based Spam Filtering and Detection Algorithms - An Efficient Analysis & Comparison
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International Journal of Engineering Trends and Technology (IJETT) | 
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| © 2013 by IJETT Journal | ||
| Volume-4 Issue-9 |
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| Year of Publication : 2013 | ||
| Authors : R.Malarvizhi , K.Saraswathi |
Citation
R.Malarvizhi , K.Saraswathi. "Content - Based Spam Filtering and Detection Algorithms - An Efficient Analysis & Comparison". International Journal of Engineering Trends and Technology (IJETT). V4(9):4237-4242 Sep 2013. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group.
Abstract
Spam is one of the major problems faced by the internet community. There are many approaches developed to overcome spam and filtering is one of the important one. The Content - based filtering is also known as cognitive filtering that recommends items based on a comparison between the content of the items and a user profile items. The content of each item is represented as a set of descriptors or terms. The terms are typically, the words that occur in a document. User profiles are represented with the same terms and built up by analyzing the content of items seen by the user. In this paper, an overview of the state of the art for spam filtering is studied and the ways of evaluation and comparison of different filt ering methods. This research paper mainly contributes to the comprehensive study of spam detection algorithms under the category of content based filtering. Then, the implemented results have been benchmarked to examine how accurately they have been classified into their original categories of spam
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Keywords
Spam, AdaBoost, KNN, Chi - Square, Black list, White list, Bayesian filters, Cache Architecture.