Research Article
Efficient E-Mail Spam Detection Strategy Using Genetic Decision Tree Processing with NLP Features
Algorithm 3
Natural Language Processing.
| start | | for each m in content: | | pCount = Σ (no. of paragraphs) | | Tokenize m by paragraph | | FakeRank = 0 | | end for | | for each paragraph in m: | | qScore = Σ (no. of paragraphs) | | if qScore > 0 | | for each quoteset | | quote_q1 classify.randomforest (quoteset_attribution_space, m) | | end if | | end for | | if quote_q1 | | A-score = A-score + 1 | | else | | A-score = A-score − 1 | | return A-score | | end if | | end for | | FakeRank = FakeRank + A-score | | if FakeRank ≥ 0 | | mLabel = real | | end if | | if FakeRank < 0 | | mLabel = fake | | end if | | end for | | end |
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