基于遗传算法的文本过滤模型及收敛性分析

摘要

For the nonlinear problem of template generation in Chinese text filtering, genetic algorithm, which could find optimal solutions within the global content, is introduced into solving text filtering problem. At the same time, a new approach based on set theory is applied to prove the theoretical feasibility, and, an adaptive strategy of genetic operators is proposed for real application. Theoretical proof and experimental results, including text classification and text information filtering by this genetic algorithm, show that the method is feasible and could obtain better information filtering results.%过滤模板的生成是网络信息过滤中一个至关重要的问题.针对模板生成中的非线性特征,借鉴遗传算法可以在全局范围内寻找最优解的特性,引入遗传算法解决文本信息过滤问题,并应用基于集合论的方法证明其理论可行性.在实际应用中,应用遗传算法生成模板进行了文本分类和文本过滤试验,并根据应用过程中存在的问题提出了遗传算子的自适应策略.理论证明以及实验结果都表明,该方法具有可行性,能够在信息过滤中取得较好的结果.