中文摘要：

当前的知识检索存在检索速度慢、效率低的问题,对此提出一种基于自然语言处理的知识检索方式,利用半监督算法进行自然语言描述,针对全部知识检索对象构建无向图,在该无向图中,设计一种标签传递方法,将有标记的数据样本传递到其余没有标记的数据样本中,完成无向图中所有数据标记的过程.利用TextRank方式,针对所有标记后的数据选取主题词,根据检索对象中的主题词实现知识检索的过程.实验结果表明,利用此算法进行知识检索,能够有效提高知识检索的速度,在短时间内完成知识检索的过程,提高用户的满意度.

英文摘要：

The current knowledge retrieval is retrieval speed is slow, the problem of low efficiency. Put forward a way of knowledge retrieval based on natural language processing, the use of a sembsupervised algorithms for natural language description, to construct knowledge retrieve objects for all undirected graph, in the undirected graph, transmission method to design a label, there will be passed to the rest of the data sample no marking data samples, complete all the data in the undirected graph marking process. Using TextRank way, in view of the data to select keywords after all the tags, according to the keywords in retrieve objects to realize the process of knowledge retrieval. The experimental results show that the algorithm presented in this paper a knowledge retrieval, can effectively improve the speed of knowledge retrieval, in a short period of time to complete the process of knowledge retrieval, improve user satisfaction.