期刊论文

中文

计算机科学

1002-137X

2011

38

6

242-245

10.3969/j.issn.1002-137X.2011.06.055

2008AA01Z131:国家高技术研究发展计划（863计划） CCNU 09A02006:中央高校基本科研业务费专项华中师范大学项目

本校为第一机构

N-gram字符是网络书写纹识别最有效的特征类型之一。针对其特征维数高、冗余特征多且无关特征少等特点,提出一种基于特征空间划分来构造集成学习分类器的网络书写纹识别方法。该方法首先根据一定的划分粒度,将初始特征集划分为等维度、无交叉的特征子集,然后基于每一个特征子集训练生成对应的基分类器(多元朴素贝叶斯),最后采用算术与几何平均相结合的融合策略完成集成学习分类器的构造。特征空间的划分(即特征子集的选择)采用遗传算法进行优化。实验在一个真实数据集上开展,其结果表明该方法有效地提高了网络书写纹的识别性能。

Online writeprint identification is a technique to identify individuals based on textual identity cues people leave behind online messages.Character N-gram is one of the most effective approaches to identify writeprint according to previous research.To deal with the high dimensional and redundant feature problems and the property of each feature being valuable for the task of writeprint identification,an ensemble learning approach based on feature subspacing was proposed in this study.The essence of this method is to partition the features into...