Based on the characteristics of high-end products,crowd-sourcing user stories can be seen as an effective means of gathering requirements,involving a large user base and generating a substantial amount of unstructured...Based on the characteristics of high-end products,crowd-sourcing user stories can be seen as an effective means of gathering requirements,involving a large user base and generating a substantial amount of unstructured feedback.The key challenge lies in transforming abstract user needs into specific ones,requiring integration and analysis.Therefore,we propose a topic mining-based approach to categorize,summarize,and rank product requirements from user stories.Specifically,after determining the number of story categories based on py LDAvis,we initially classify“I want to”phrases within user stories.Subsequently,classic topic models are applied to each category to generate their names,defining each post-classification user story category as a requirement.Furthermore,a weighted ranking function is devised to calculate the importance of each requirement.Finally,we validate the effectiveness and feasibility of the proposed method using 2966 crowd-sourced user stories related to smart home systems.展开更多
The weapon and equipment operational requirement analysis(WEORA) is a necessary condition to win a future war,among which the acquisition of knowledge about weapons and equipment is a great challenge. The main challen...The weapon and equipment operational requirement analysis(WEORA) is a necessary condition to win a future war,among which the acquisition of knowledge about weapons and equipment is a great challenge. The main challenge is that the existing weapons and equipment data fails to carry out structured knowledge representation, and knowledge navigation based on natural language cannot efficiently support the WEORA. To solve above problem, this research proposes a method based on question answering(QA) of weapons and equipment knowledge graph(WEKG) to construct and navigate the knowledge related to weapons and equipment in the WEORA. This method firstly constructs the WEKG, and builds a neutral network-based QA system over the WEKG by means of semantic parsing for knowledge navigation. Finally, the method is evaluated and a chatbot on the QA system is developed for the WEORA. Our proposed method has good performance in the accuracy and efficiency of searching target knowledge, and can well assist the WEORA.展开更多
目的评价“互联网+”护理服务模式对脑卒中患者康复结局的影响。方法系统检索CNKI、万方、维普、PubMed、Web of Science等权威数据库中有关“互联网+”护理服务模式对脑卒中患者康复结局的研究,检索时间为建库至2021年8月,运用State 1...目的评价“互联网+”护理服务模式对脑卒中患者康复结局的影响。方法系统检索CNKI、万方、维普、PubMed、Web of Science等权威数据库中有关“互联网+”护理服务模式对脑卒中患者康复结局的研究,检索时间为建库至2021年8月,运用State 12.0对符合纳入标准的文献进行系统评价,通过计算均数差值及其置信区间进行判断。结果共纳入27篇文献,共有脑卒中患者3030例。分析结果显示,“互联网+”护理服务可以有效提高卒中患者康复期间的日常生活能力[加权均数差值(WMD)为11.38,95%CI为8.60~14.15]、运动功能(WMD=10.14,95%CI为7.82~12.45)、平衡功能(WMD=4.84,95%CI为1.52~8.16)、心理状况[标准均数差值(SMD)为3.32,95%CI为0.47~6.16]、焦虑(SMD=-1.08,95%CI为-1.77~-0.39)、抑郁(SMD=-1.18,95%CI为-1.80~-0.56)、生活质量(SMD=9.87,95%CI为6.84~12.89)、认知水平(SMD=1.80,95%CI为0.69~2.91)。结论“互联网+”护理服务模式为改善脑卒中患者康复效果、助力其回归社区和家庭提供了良好的渠道。展开更多
基金supported by the National Natural Science Foundation of China(71690233,71901214)。
文摘Based on the characteristics of high-end products,crowd-sourcing user stories can be seen as an effective means of gathering requirements,involving a large user base and generating a substantial amount of unstructured feedback.The key challenge lies in transforming abstract user needs into specific ones,requiring integration and analysis.Therefore,we propose a topic mining-based approach to categorize,summarize,and rank product requirements from user stories.Specifically,after determining the number of story categories based on py LDAvis,we initially classify“I want to”phrases within user stories.Subsequently,classic topic models are applied to each category to generate their names,defining each post-classification user story category as a requirement.Furthermore,a weighted ranking function is devised to calculate the importance of each requirement.Finally,we validate the effectiveness and feasibility of the proposed method using 2966 crowd-sourced user stories related to smart home systems.
文摘The weapon and equipment operational requirement analysis(WEORA) is a necessary condition to win a future war,among which the acquisition of knowledge about weapons and equipment is a great challenge. The main challenge is that the existing weapons and equipment data fails to carry out structured knowledge representation, and knowledge navigation based on natural language cannot efficiently support the WEORA. To solve above problem, this research proposes a method based on question answering(QA) of weapons and equipment knowledge graph(WEKG) to construct and navigate the knowledge related to weapons and equipment in the WEORA. This method firstly constructs the WEKG, and builds a neutral network-based QA system over the WEKG by means of semantic parsing for knowledge navigation. Finally, the method is evaluated and a chatbot on the QA system is developed for the WEORA. Our proposed method has good performance in the accuracy and efficiency of searching target knowledge, and can well assist the WEORA.
文摘目的评价“互联网+”护理服务模式对脑卒中患者康复结局的影响。方法系统检索CNKI、万方、维普、PubMed、Web of Science等权威数据库中有关“互联网+”护理服务模式对脑卒中患者康复结局的研究,检索时间为建库至2021年8月,运用State 12.0对符合纳入标准的文献进行系统评价,通过计算均数差值及其置信区间进行判断。结果共纳入27篇文献,共有脑卒中患者3030例。分析结果显示,“互联网+”护理服务可以有效提高卒中患者康复期间的日常生活能力[加权均数差值(WMD)为11.38,95%CI为8.60~14.15]、运动功能(WMD=10.14,95%CI为7.82~12.45)、平衡功能(WMD=4.84,95%CI为1.52~8.16)、心理状况[标准均数差值(SMD)为3.32,95%CI为0.47~6.16]、焦虑(SMD=-1.08,95%CI为-1.77~-0.39)、抑郁(SMD=-1.18,95%CI为-1.80~-0.56)、生活质量(SMD=9.87,95%CI为6.84~12.89)、认知水平(SMD=1.80,95%CI为0.69~2.91)。结论“互联网+”护理服务模式为改善脑卒中患者康复效果、助力其回归社区和家庭提供了良好的渠道。
