关键词: String Kernel, 核主成分分析, 负实例, 特征提取

Abstract: This paper presents a method that translates false instance in grammatical database to kernel matrix through String Kernel，and uses KPCA to extract feature of the translated kernel matrix.We can separate the original false instance database into many small characteristic tables according to these extracted features，and design a classified machine by constructing false instance characteristic table.A new sentence is distributed to some characteristic table for matching of false instance through this classification machine.For characteristic table is much little than original false instance database，the running speed is enhanced very much without decreasing the accuracy of grammatical check.By compared with grammar inspection function of word，the new system demonstrates more quick speed while keeping the accuracy of grammatical check

Key words: String Kernel, Kernel Principal Component Analysis（KPCA), false instance, feature extraction