面向大规模网络数据的社会化问答系统

为研究面向大规模网络数据的社会化问答系统(Social Question and Answer System,SocialQA).分别描述了问答系统的各个组成技术:1)问句预处理:问句分析和问句扩展.2)问句匹配.本文在1500万个网络问答数据集上,进行了问句匹配的实验.实验表明:在封闭测试中,问句匹配的准确率,达到了90%以上,在开放测试中,问句匹配的准确率达到了70%以上,很好地满足了系统的精度和实时性的要求.     

Multi-feature integration kernel particle filtering target tracking

In light of degradation of particle filtering and robust weakness in the utilization of single feature tracking,this paper presents a kernel particle filtering tracking method based on multi-feature in...     

负离子助剂对聚丙烯综合性能的影响

本文通过研究主要成分为二氧化钛(TiO_2),并含有Zn.Ce.Si.Ba.Nb.Th元素的负离子助剂(FL助剂)添加至聚丙烯(PP)中,不同粒径,不同添加量对PP综合性能的影响,最终确定最经济的粒径和添加量.     

Feature selection algorithm for text classification based on improved mutual information

In order to solve the poor performance in text classification when using traditional formula of mutual information (MI),a feature selection algorithm were proposed based on improved mutual information.The improved mutual information algorithm,which is on the basis of traditional improved mutual information methods that enhance the MI value of negative characteristics and feature’s frequency,supports the concept of concentration degree and dispersion degree.In accordance with the concept of concentration degree and dispersion degree,formulas which embody concentration degree and dispersion degree were constructed and the improved mutual information was implemented based on these.In this paper,the feature selection algorithm was applied based on improved mutual information to a text classifier based on Biomimetic Pattern Recognition and it was compared with several other feature selection methods.The experimental results showed that the improved mutual information feature selection method greatly enhances the performance compared with traditional mutual information feature selection methods and the performance is better than that of information gain.Through the introduction of the concept of concentration degree and dispersion degree,the improved mutual information feature selection method greatly improves the performance of text classification system.     

负离子助剂对聚丙烯综合性能的影响

本文通过研究主要成分为二氧化钛(TiO2),并含有Zn、Ce、Si、Ba、Nb、Th等元素的负离子助剂(FL助剂)添加至聚丙烯(PP)中,不同粒径,不同添加量对PP综合性能的影响,最终确定最经济的粒径和添加量.     

可拓神经网络模型的设计与实现

为解决BP神经网络模式识别时训练准则和分类准则不一致的问题,采用可拓学的扩缩变换,通过在输出空间中用一个特定区域(称作教师区域)来代替教师信号,极大地提高了可拓神经网络模型的训练速度,同时彻底解决网络训练和实际分类准则不一致的问题.计算实例表明,可拓神经网络是一个有效的模式识别工具.