摘要
为了让计算机具有处理甚至理解自然语言的能力,人们发明了很多自然语言语义分析理论。但是应用在电力系统工作票和操作票的领域中还很少。在中文分词的理论基础上利用正向最大匹配算法,针对电厂两票安全措施的语句进行自动识别,并分析了两票安全措施语句的语意。结果表明基于两票填写内容=动作词+设备名称词+状态词这种表示结构下,计算机能够很好的识别和理解电厂两票安全措施。这样计算机系统就能够对电力两票知识进一步的计算和推理,从而为深度人工智能开票提供了广泛的应用前景。
In order to make computer have the ability of processing and even comprehending natural language, lots of natural language semantic analyzing theories have been developed. But the application in the field of power sys- tem work votes and operating votes is little. On the basis of Chinese word segmentation theory, the power two-ticket safety measures can be automatically identified by the optimized partition--forward maximum matching algorithm, and the two-ticket safety measures statements semantic can be analysed. The results show that based on this structure, the word of two votes = action words＋ device name words ＋ status word, the computer is able to identify and under- stand the safety measures of the power two-ticket, so that computer system can carry out the calculation of the power two votes safety measures and reasoning, which provides a wide range of application prospects for the depth of artifi- cial intelligence provide ticket.
出处
《计算机仿真》
CSCD
北大核心
2014年第1期145-148,355,共5页
Computer Simulation
关键词
自然语言理解
中文分词
正向最大匹配
电力两票系统
Natural language understanding
Chinese word segmentation
forward maximum matching algorithm
two-ticket system
