摘要
构建基于自然语言处理的案例学习模型,以文本形式描述的船舶避碰案例,通过自动分词、消岐和语义分析等步骤,从中提取和生成以框架形式描述的避碰案例,并将其存储在计算机中。仿真试验表明,该模型可以实现避碰案例从文本文件到可用案例的有效转换,为案例学习提供新的方法。
A case learning model based on natural language processing was established. The model can extract and generate collision avoidance case which described by frame model and also can store it into computer from ship collision avoidance case which described in text by automatic word segmentation, ambiguity resolution semantic analysis and so on. Simulation test showed that the model can realize effectively conversion from text file to useful case, and find a new way to case learning.
出处
《船海工程》
2010年第1期110-114,共5页
Ship & Ocean Engineering
基金
霍英东教育基金会项目(101079)
上海市教育委员会科研项目(06FZ016)
关键词
船舶避碰
案例学习
自动文本分析
自然语言处理
自动分词
ship collision avoidance
case learning
automatic text analysis
natural language processing
automatic word segmentation
