论文部分内容阅读
论文介绍了一种具有自学习能力的中文交互式网络搜索引擎INSE(aninteractivenetsearchengineforChi-nesetext),向量空间模型、基于自动机思想的中文分词技术和神经网络BP算法的应用是INSE的主要特点,重点讨论了INSE的自学习能力。基于自动机思想分词是INSE提出的新概念,应用于中文分词可以满足最大匹配且速度较快。INSE自学习能力的实现依靠神经网络的BP算法。该算法应用于交互式网络搜索引擎可以提供更加精确的查询结果。
The paper introduces a kind of Chinese interactive web search engine with auto-learning ability, INSE (aninteractivenetsearchengineforChi-nesetext), vector space model, automaton-based Chinese word segmentation and BP neural network algorithm are the main features of INSE, focusing on INSE self-learning ability. Based on automaton thought segmentation is a new concept proposed by INSE, applied to Chinese word segmentation to meet the maximum match and faster. The realization of INSE self-learning ability depends on the BP algorithm of neural network. The algorithm used in interactive web search engine can provide more accurate query results.