Student selection is of crucial importance for supervisors who are choosing students for postgraduate studies or research projects.Due to the challenge of asymmetric information,it is difficult for them to find suitab...Student selection is of crucial importance for supervisors who are choosing students for postgraduate studies or research projects.Due to the challenge of asymmetric information,it is difficult for them to find suitable candidates.The existing methods do not work so well in the web 2.0 context which is inundated with vast online information.In order to overcome the deficiency,a research social network enhanced approach is proposed to provide decision support.It appeals to supervisors to adopt the proposed user-driven social marketing strategy.Meanwhile,this study mainly presents a system-driven personalized recommendation approach to support supervisors'decisions of student selection.The proposed method distinguishes supervisors based on their co-author networks to extract their potential preferences of collaboration styles.Subsequently,corresponding recommendation strategies are employed to provide personalized student recommendation services for targeted supervisors.A prototype is implemented on ScholarMate which provides online communication channels for researchers.A user study is conducted to verify the effectiveness of the proposed approach.The results enlighten designers to consider the differences among different users when designing recommendation strategies.展开更多
当今世界由于经济、科技、地缘战略、国际秩序等问题频繁爆发冲突事件,冲突规模正由个体冲突、小规模群体冲突向复杂大规模群体冲突转变。相较于个体间的冲突,大规模群体冲突事件持续时间更长、波及范围更广,易对我国的社会秩序以及经...当今世界由于经济、科技、地缘战略、国际秩序等问题频繁爆发冲突事件,冲突规模正由个体冲突、小规模群体冲突向复杂大规模群体冲突转变。相较于个体间的冲突,大规模群体冲突事件持续时间更长、波及范围更广,易对我国的社会秩序以及经济发展造成恶劣影响。图模型冲突分析(Graph model for conflict resolution,GMCR)理论提供了分析冲突、解决矛盾的有效方案,作为一门专业解决冲突问题的理论工具已经在水资源、环境管理和经济政策等领域得到广泛应用,并取得良好效果。然而,随着冲突事件参与者日渐增多、主体的策略日趋复杂形成了指数级增加的局势,以及主体的偏好行为不确定性加强,传统的决策支持系统GMCRⅡ难以求解此类复杂冲突问题。基于强度偏好冲突分析理论的代数表达,开发了基于.NET平台的冲突分析WEB系统SP-GMCRDSS,该系统包括可行状态生成、状态转移设置、强度偏好序列生成和稳定性分析引擎4个模块,对比现有的系统,SP-GMCRDSS能更高效地辅助冲突分析者解决数据驱动下的大型、复杂的冲突。并且运用文本挖掘技术提取决策者策略数据,辅助分析者确定决策支持系统建模信息的输入,降低模型构建的主观性。最后,通过“兰州水污染冲突事件”演示了该系统的建模、求解以及分析的功能。展开更多
基金Fujian Provincial Education Department Project,China(No.JAS180414)Putian University Project,China(No.2018061)Fujian Provincial Social Science Project,China(No.FJ2017C009)。
文摘Student selection is of crucial importance for supervisors who are choosing students for postgraduate studies or research projects.Due to the challenge of asymmetric information,it is difficult for them to find suitable candidates.The existing methods do not work so well in the web 2.0 context which is inundated with vast online information.In order to overcome the deficiency,a research social network enhanced approach is proposed to provide decision support.It appeals to supervisors to adopt the proposed user-driven social marketing strategy.Meanwhile,this study mainly presents a system-driven personalized recommendation approach to support supervisors'decisions of student selection.The proposed method distinguishes supervisors based on their co-author networks to extract their potential preferences of collaboration styles.Subsequently,corresponding recommendation strategies are employed to provide personalized student recommendation services for targeted supervisors.A prototype is implemented on ScholarMate which provides online communication channels for researchers.A user study is conducted to verify the effectiveness of the proposed approach.The results enlighten designers to consider the differences among different users when designing recommendation strategies.
文摘当今世界由于经济、科技、地缘战略、国际秩序等问题频繁爆发冲突事件,冲突规模正由个体冲突、小规模群体冲突向复杂大规模群体冲突转变。相较于个体间的冲突,大规模群体冲突事件持续时间更长、波及范围更广,易对我国的社会秩序以及经济发展造成恶劣影响。图模型冲突分析(Graph model for conflict resolution,GMCR)理论提供了分析冲突、解决矛盾的有效方案,作为一门专业解决冲突问题的理论工具已经在水资源、环境管理和经济政策等领域得到广泛应用,并取得良好效果。然而,随着冲突事件参与者日渐增多、主体的策略日趋复杂形成了指数级增加的局势,以及主体的偏好行为不确定性加强,传统的决策支持系统GMCRⅡ难以求解此类复杂冲突问题。基于强度偏好冲突分析理论的代数表达,开发了基于.NET平台的冲突分析WEB系统SP-GMCRDSS,该系统包括可行状态生成、状态转移设置、强度偏好序列生成和稳定性分析引擎4个模块,对比现有的系统,SP-GMCRDSS能更高效地辅助冲突分析者解决数据驱动下的大型、复杂的冲突。并且运用文本挖掘技术提取决策者策略数据,辅助分析者确定决策支持系统建模信息的输入,降低模型构建的主观性。最后,通过“兰州水污染冲突事件”演示了该系统的建模、求解以及分析的功能。
