Fuzzy Similarity and ID3 Algorithm for Anti-Spam Filtering

Provided by: International Journal of Engineering Associates
Topic: Security
Format: PDF
The task of anti-spam filter is to rule out unsolicited bulk e-mail (junk) automatically from a user's mail stream. The two approaches that are used for classification here are based on the fuzzy and decision trees to build an automatic anti-spam filter to classify emails as spam or legitimate. Fuzzy similarity and ID3 approach based systems derives the classification from training data using learning techniques. The fuzzy based method uses fuzzy sets and the decision tree method uses a set of heuristic rules to classify e-mail messages. For each method a grade of certainty is computed where in fuzzy logic by using fuzzy similarity measure and in ID3 by using information gain and entropy values.

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