[1]王定桥,李卫华,杨春燕.从用户需求语句建立问题可拓模型的研究[J].智能系统学报编辑部,2015,10(6):865-871.[doi:10.11992/tis.201507038]
WANG Dingqiao,LI Weihua,YANG Chunyan.Research on building an extension model from user requirements[J].CAAI Transactions on Intelligent Systems,2015,10(6):865-871.[doi:10.11992/tis.201507038]
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WANG Dingqiao,LI Weihua,YANG Chunyan.Research on building an extension model from user requirements[J].CAAI Transactions on Intelligent Systems,2015,10(6):865-871.[doi:10.11992/tis.201507038]
从用户需求语句建立问题可拓模型的研究
《智能系统学报》编辑部[ISSN 1673-4785/CN 23-1538/TP] 卷:
10
期数:
2015年第6期
页码:
865-871
栏目:
学术论文—自然语言处理与理解
出版日期:
2015-12-25
- Title:
- Research on building an extension model from user requirements
- Keywords:
- extenics; extension model; extension strategy generation; information extraction; classification
- 分类号:
- TP391
- 摘要:
- 准确地建立待解决问题的可拓模型是可拓策略生成的关键步骤。目前的可拓策略生成系统在建立可拓模型时因自然语言理解的困难,未能充分理解用户需求,所以较难自动建立问题的可拓模型。提出了解析用户自然语言需求语句、并自动建立可拓模型的方法。该方法的核心包括4步:1)对用户需求语句进行组块分析得到短语序列;2)对短语序列进行分类;3)使用匹配规则抽取分类后的短语,得到便于计算机处理的需求信息;4)结合数据库技术进行可拓模型的建立。以租房问题为案例,实现了该方法。实验结果表明,该方法能较好地理解用户需求信息并成功建立租房问题可拓模型。
- Abstract:
- Building an effective extension model to solve a problem is a key step in generating an extension strategy. Due to the complexity of natural language processing, the current extension strategy generation system is insufficiently clear with respect to user requirements, so it is hard to automatically build an extension model. In this paper, we propose a method for parsing the user requirement sentence in order to then automatically build the extension model. This method contains four core steps. First, chunk parsing is performed on the sentence containing the user requirements to obtain the phrase sequence. Secondly, the phrase sequence is classified with a classifier. Thirdly, based on the matching rule, information is extracted from the classified phrase to obtain the information required for computer processing. Next, database technology is used to build the extension model. Using a tenement building as an example, we implemented and tested our proposed method. Based on our experimental results, we proved that the proposed method is effective for understanding user requirements in order to build an extension model.
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-
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备注/Memo
收稿日期:2015-07-23;改回日期:。
基金项目:国家自然科学基金资助项目(61273306).
作者简介:王定桥,男,1988年生,硕士研究生,主要研究方向为智能软件。李卫华,女,1957年生,教授,硕士生导师,主要研究方向为面向Agent计算、网络信息系统、智能软件,发表学术论文40余篇。
通讯作者:王定桥.E-mail:wangdingqiao2012@qq.com.
更新日期/Last Update:
1900-01-01