Title of article :
Optimising anti-spam filters with evolutionary algorithms
Author/Authors :
Yevseyeva، نويسنده , , Iryna and Basto-Fernandes، نويسنده , , Vitor and Ruano-Ordلs، نويسنده , , David A. Mendez، نويسنده , , José R.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2013
Abstract :
This work is devoted to the problem of optimising scores for anti-spam filters, which is essential for the accuracy of any filter based anti-spam system, and is also one of the biggest challenges in this research area. In particular, this optimisation problem is considered from two different points of view: single and multiobjective problem formulations. Some of existing approaches within both formulations are surveyed, and their advantages and disadvantages are discussed. Two most popular evolutionary multiobjective algorithms and one single objective algorithm are adapted to optimisation of the anti-spam filters’ scores and compared on publicly available datasets widely used for benchmarking purposes. This comparison is discussed, and the recommendations for the developers and users of optimising anti-spam filters are provided.
Keywords :
Multiobjective optimisation , Evolutionary Computation , Anti-spam filters , Genetic algorithms
Journal title :
Expert Systems with Applications
Journal title :
Expert Systems with Applications