Improved Bayesian-Based Spam Filtering Approach
| Autor: | Jun Kai Yi, Xue Jiang |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
A priori probability
business.industry Computer science Bayesian probability General Medicine Filter (signal processing) computer.software_genre Machine learning Field (computer science) Bag-of-words model Data mining Artificial intelligence business Recursive Bayesian estimation computer Selection (genetic algorithm) |
| Zdroj: | Applied Mechanics and Materials. :1885-1891 |
| ISSN: | 1662-7482 |
| DOI: | 10.4028/www.scientific.net/amm.401-403.1885 |
| Popis: | Bayesian filtering approach is widely used in the field of anti-spam now. However, the two assumptions of this algorithm are significantly different with the actual situation so as to reduce the accuracy of the algorithm. This paper proposes a detailed improvement on researching of Bayesian Filtering Algorithm principle and implement method. It changes the priori probability of spam from constant figure to the actual probability, improves selection and selection rules of the token, and also adds URL and pictures to the detection content. Finally it designs a spam filter based on improved Bayesian filter approach. The experimental result of this improved Bayesian Filter approach indicates that it has a beneficial effect in the spam filter application. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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