Current workflow management systems usually adopt the existing technologies such as TCP/IP-based Web technologies and CORBA as well to fulfill the bottom communications. Very often it has been considered only from a t...Current workflow management systems usually adopt the existing technologies such as TCP/IP-based Web technologies and CORBA as well to fulfill the bottom communications. Very often it has been considered only from a theoretical point of view, mainly for the lack of concrete possibilities to execute with elasticity. MAT (Mobile Agent Technology) represents a very attractive approach to the distributed control of computer networks and a valid alternative to the implementation of strategies for workflow system. This paper mainly focuses on improving the performance of workflow system by using MAT. Firstly, the performances of workflow systems based on both CORBA and mobile agent are summarized and analyzed; Secondly, the performance contrast is presented by introducing the mathematic model of each kind of data interaction process respectively. Last, a mobile agentbased workflow system named MAWMS is presented and described in detail. Key words workflow - Mobile Agent - Contract Net Protocol - CORBA - Web CLC number TP 393 Foundation item: Supported by the National Natural Science Foundation of China (60272024) and National Natural Science Foundation of Henan Province (0411014100)Biography: LI Jie, (1975-), male, lector, Ph. D., research direction: workflow, mobile agent, network management.展开更多
人工智能技术在教育领域的深度应用,已成为国家教育数字化转型的核心战略。在计算机实践教学领域,实践学习资料的精准推荐是提升学生学习效能与质量的重要途径。针对高校教育规模化与学生需求多元化之间的矛盾,提出一种基于轻量级教育...人工智能技术在教育领域的深度应用,已成为国家教育数字化转型的核心战略。在计算机实践教学领域,实践学习资料的精准推荐是提升学生学习效能与质量的重要途径。针对高校教育规模化与学生需求多元化之间的矛盾,提出一种基于轻量级教育大模型的个性化实践学习资料推荐模型LightPLRec(Lightweight Personalized Learning Recommender for Dynamic Practice Materials),旨在依据学生个体特征的动态变化智能推荐个性化的实践学习资料。基于低算力需求的轻量级大模型,通过指令微调和强化学习方法构建了面向个性化实践学习资料推荐的教育大模型SPIR(Student Profile&Interest-based Re-commender)。通过整合多源异构数据,深度融入课程知识体系、学科前沿动态、产业发展趋势、国家战略导向,构建了跨学科、多模态的实践学习资料库,并设计了图转主题文本方法gragh2topic。依托于SPIR大模型的强大赋能和多源资料库的坚实支撑,提出了基于智能工作流的资料推荐方法。设计主题分析方法从学生能力评估结果中提取学生的能力特征,应用图卷积网络算法GCN从学生学习行为数据中挖掘学生的兴趣特征,创建了“能力-推荐智能体”和“兴趣-推荐智能体”,构建了双智能体协同驱动的智能化流程体系,实现了从学生个性化画像智能生成到实践学习资料动态推荐的系列工作流任务;并且构建了个性化资料推荐数据集,在该数据集上验证了所提模型的性能显著优于基线模型。其中,以Qwen2.5-3.0B为基模型训练的LightPLRec模型,在能力推荐与兴趣推荐这两项任务中展现出卓越性能,准确率分别高达0.947和0.939,其表现均优于DeepSeek-V3在同一数据集上的测评结果。该研究为教育大模型的垂直场景应用提供了技术范式,同时通过创建个性化实践学习资料动态推荐模型,为践行“因材施教”理念和培育高素质计算机实践人才提供了创新路径。展开更多
文摘Current workflow management systems usually adopt the existing technologies such as TCP/IP-based Web technologies and CORBA as well to fulfill the bottom communications. Very often it has been considered only from a theoretical point of view, mainly for the lack of concrete possibilities to execute with elasticity. MAT (Mobile Agent Technology) represents a very attractive approach to the distributed control of computer networks and a valid alternative to the implementation of strategies for workflow system. This paper mainly focuses on improving the performance of workflow system by using MAT. Firstly, the performances of workflow systems based on both CORBA and mobile agent are summarized and analyzed; Secondly, the performance contrast is presented by introducing the mathematic model of each kind of data interaction process respectively. Last, a mobile agentbased workflow system named MAWMS is presented and described in detail. Key words workflow - Mobile Agent - Contract Net Protocol - CORBA - Web CLC number TP 393 Foundation item: Supported by the National Natural Science Foundation of China (60272024) and National Natural Science Foundation of Henan Province (0411014100)Biography: LI Jie, (1975-), male, lector, Ph. D., research direction: workflow, mobile agent, network management.
文摘人工智能技术在教育领域的深度应用,已成为国家教育数字化转型的核心战略。在计算机实践教学领域,实践学习资料的精准推荐是提升学生学习效能与质量的重要途径。针对高校教育规模化与学生需求多元化之间的矛盾,提出一种基于轻量级教育大模型的个性化实践学习资料推荐模型LightPLRec(Lightweight Personalized Learning Recommender for Dynamic Practice Materials),旨在依据学生个体特征的动态变化智能推荐个性化的实践学习资料。基于低算力需求的轻量级大模型,通过指令微调和强化学习方法构建了面向个性化实践学习资料推荐的教育大模型SPIR(Student Profile&Interest-based Re-commender)。通过整合多源异构数据,深度融入课程知识体系、学科前沿动态、产业发展趋势、国家战略导向,构建了跨学科、多模态的实践学习资料库,并设计了图转主题文本方法gragh2topic。依托于SPIR大模型的强大赋能和多源资料库的坚实支撑,提出了基于智能工作流的资料推荐方法。设计主题分析方法从学生能力评估结果中提取学生的能力特征,应用图卷积网络算法GCN从学生学习行为数据中挖掘学生的兴趣特征,创建了“能力-推荐智能体”和“兴趣-推荐智能体”,构建了双智能体协同驱动的智能化流程体系,实现了从学生个性化画像智能生成到实践学习资料动态推荐的系列工作流任务;并且构建了个性化资料推荐数据集,在该数据集上验证了所提模型的性能显著优于基线模型。其中,以Qwen2.5-3.0B为基模型训练的LightPLRec模型,在能力推荐与兴趣推荐这两项任务中展现出卓越性能,准确率分别高达0.947和0.939,其表现均优于DeepSeek-V3在同一数据集上的测评结果。该研究为教育大模型的垂直场景应用提供了技术范式,同时通过创建个性化实践学习资料动态推荐模型,为践行“因材施教”理念和培育高素质计算机实践人才提供了创新路径。
