Motor insurance knowledge management in AIML format using tree structured dictionary mechanism and conceptual graph

Wilailuk Sukfong, S. Nakkrasae, Preecha Panpipat
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Abstract

Nowadays, information providers of car insurance through the site are not effective enough for consumers needs. Thus, this paper presents a motor insurance knowledge management based on Artificial Intelligence Markup Language (AIML). In the part of knowledge management, tree structure dictionary mechanism method is used for word segmentation and the conversion technique to correct grammatical sentences (Pattern Normalization) utilizes conceptual graphs. Motor insurance enquiry intelligent system via mobile devices is then implemented. It is analyzed and designed by using object-oriented approach with UML (Unified Modeling Language). The result shows that the developed system can be used for answer questions and works more efficiently.
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采用树状字典机制和概念图实现AIML格式的车险知识管理
目前,车险信息提供者通过网站提供的信息还不足以满足消费者的需求。为此,本文提出了一种基于人工智能标记语言(AIML)的车险知识管理方法。在知识管理部分,使用树形结构词典机制方法进行分词,使用概念图转换技术(模式归一化)纠正语法句子。通过移动设备实现汽车保险查询智能系统。采用面向对象的方法,结合UML(统一建模语言)对其进行了分析和设计。结果表明,所开发的系统可以用于答疑,工作效率更高。
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