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Semantic analysis of natural language software requirement

机译:自然语言软件需求的语义分析

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In the recent past, domain specific solutions for detailed semantic analysis have got acceptable by natural language processing community and use of applications involving natural language based user interface. Different approaches that has been previously used is focusing on quality of text and improving the text contents by adding semantic information with text then the existing approaches used for semantic analysis can provide better results. In this, an approach was presented to address the problem of non-availability of semantic information required for better semantic analysis. This problem is solved by using semantic technology to annotate text of software requirements expressed in a natural language with their domain specific semantics and investigate the effect of semantic analysis with attached semantics. The presented approach uses a semantic framework specifically designed for interpretation and detailed semantic analysis of natural language software requirement specifications. The used framework is based on semantic technology involves knowledge extracted from existing software requirement documents and knowledge extracted from existing applications. The presented approach shows that by adapting and combing existing ontologies to support knowledge management, developing system and performing experiments on requirement of real world software systems. In this approach start with software requirement specification, after this clean the irrelevant requirements, convert the cleaned requirements into graph that represents inter related different elements. Represent the requirement graph into sparse matrix, after these all steps; we generate ontology with the help of OntoGen tool.
机译:在最近的过去,用于特定语义分析的领域特定解决方案已被自然语言处理社区和涉及基于自然语言的用户界面的应用程序使用接受。先前已使用的不同方法着重于文本的质量并通过在文本中添加语义信息来改善文本内容,然后用于语义分析的现有方法可以提供更好的结果。在这种情况下,提出了一种方法来解决更好的语义分析所需的语义信息不可用的问题。通过使用语义技术对具有自然语言表达的软件需求的文本及其领域特定的语义进行注释,并研究带有附加语义的语义分析的效果,可以解决此问题。提出的方法使用专门设计用于自然语言软件需求规范的解释和详细语义分析的语义框架。使用的框架基于语义技术,涉及从现有软件需求文档中提取的知识和从现有应用程序中提取的知识。提出的方法表明,通过适应和组合现有的本体以支持知识管理,开发系统并根据实际软件系统的要求进行实验。在这种方法中,从软件需求规范开始,在清除了不相关的需求之后,将清除的需求转换为表示相互关联的不同元素的图形。完成所有这些步骤后,将需求图表示为稀疏矩阵;我们借助OntoGen工具生成本体。

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