安全关键软件需求中的相关知识大多需要手工提取,既费时又费力。近年来,人工智能技术逐渐被应用于安全关键软件设计与开发过程中,以减少工程师的手工劳动,缩短软件开发的生命周期。文中提出了一种安全关键软件术语推荐和需求分类方法,...安全关键软件需求中的相关知识大多需要手工提取,既费时又费力。近年来,人工智能技术逐渐被应用于安全关键软件设计与开发过程中,以减少工程师的手工劳动,缩短软件开发的生命周期。文中提出了一种安全关键软件术语推荐和需求分类方法,为安全关键软件需求规约提供了基础。首先,基于词性规则和依存句法规则对候选术语进行提取,通过术语相似度计算和聚类方法对候选术语进行聚类,将聚类结果推荐给工程师;其次,基于特征提取方法和分类方法将安全关键软件需求自动分为功能、安全性、可靠性等需求;最后,在AADL(Architecture Analysis and Design Language)开源建模环境OSATE中实现了原型工具TRRC4SCSTool,并基于工业界案例需求、安全分析与认证标准等构建实验数据集进行了实验验证,证明了所提方法的有效性。展开更多
The construction of virtual community in foreign language learning is a comprehensive foreign language learning environment integrated with foreign language vocabulary database construction and vocabulary retrieval, c...The construction of virtual community in foreign language learning is a comprehensive foreign language learning environment integrated with foreign language vocabulary database construction and vocabulary retrieval, combining the virtual reality technology to construct the language environment of foreign language learning. The virtual community of foreign language leaming can improve the sense of language authenticity in foreign language learning and improve the quality of foreign language teaching. A method of building a virtual community for foreign language learning is proposed based on data mining technology, data acquisition and feature preprocessing model for building semantic vocabulary of foreign language learning is constructed, the linguistic environment characteristics of the semantic vocabulary data of foreign language learning is analyzed, and the semantic noumenon structure model is obtained. Fuzzy clustering method is used for vocabulary clustering and comprehensive retrieval in the virtual community of foreign language learning, the performance of vocabulary classification in foreign language learning is improved, the adaptive semantic information fusion method is used to realize the vocabulary data mining in the virtual community of foreign language learning, information retrieval and access scheduling for virtual communities in foreign language learning are realized based on data mining results. The simulation results show that the accuracy of foreign language vocabulary retrieval is good, improve the efficiency of foreign language learning.展开更多
文摘安全关键软件需求中的相关知识大多需要手工提取,既费时又费力。近年来,人工智能技术逐渐被应用于安全关键软件设计与开发过程中,以减少工程师的手工劳动,缩短软件开发的生命周期。文中提出了一种安全关键软件术语推荐和需求分类方法,为安全关键软件需求规约提供了基础。首先,基于词性规则和依存句法规则对候选术语进行提取,通过术语相似度计算和聚类方法对候选术语进行聚类,将聚类结果推荐给工程师;其次,基于特征提取方法和分类方法将安全关键软件需求自动分为功能、安全性、可靠性等需求;最后,在AADL(Architecture Analysis and Design Language)开源建模环境OSATE中实现了原型工具TRRC4SCSTool,并基于工业界案例需求、安全分析与认证标准等构建实验数据集进行了实验验证,证明了所提方法的有效性。
文摘The construction of virtual community in foreign language learning is a comprehensive foreign language learning environment integrated with foreign language vocabulary database construction and vocabulary retrieval, combining the virtual reality technology to construct the language environment of foreign language learning. The virtual community of foreign language leaming can improve the sense of language authenticity in foreign language learning and improve the quality of foreign language teaching. A method of building a virtual community for foreign language learning is proposed based on data mining technology, data acquisition and feature preprocessing model for building semantic vocabulary of foreign language learning is constructed, the linguistic environment characteristics of the semantic vocabulary data of foreign language learning is analyzed, and the semantic noumenon structure model is obtained. Fuzzy clustering method is used for vocabulary clustering and comprehensive retrieval in the virtual community of foreign language learning, the performance of vocabulary classification in foreign language learning is improved, the adaptive semantic information fusion method is used to realize the vocabulary data mining in the virtual community of foreign language learning, information retrieval and access scheduling for virtual communities in foreign language learning are realized based on data mining results. The simulation results show that the accuracy of foreign language vocabulary retrieval is good, improve the efficiency of foreign language learning.
