In this paper, we proposed an automatic keyword extraction method based on KNN method.
本文利用K最近邻方法的思想，提出了一种基于K最近邻的关键词自动抽取方法。
We divide the system into four main tasks: word segment and sentence segment, syntax analysis, keyword extraction and sentence similarity computing.
本文将阅卷过程分解为四个主要任务来进行的：分句分词、句法分析、关键词提取和相似度计算。
This paper mainly focuses on question analysis and answer extraction. Question analysis includes question classification, keyword extraction and keyword expansion.
本文主要研究了问答系统的问题理解与答案抽取两个部分。
With the current technology of Information Retrieval, this paper proposes a method of automatic keyword extraction from massive data sets based on feature combination.
本文利用现有的信息检索技术，对海量数据集上自动抽取关键词问题进行了研究，给出了一个基于特征组合的关键词自动抽取方法。
It constructs document feature vector of subject and Keyword separately by using a new method of document feature extraction.
使用新的文档特征抽取方法构造了文档的主题和关键字特征向量。
It constructs document feature vector of subject and Keyword separately by using a new method of document feature extraction.
使用新的文档特征抽取方法构造了文档的主题和关键字特征向量。
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