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情境信息及其在智慧学习资源推荐中的应用研究 被引量:15

A Study of Context Information and its Applications in the Recommendation of Smart Learning Resources
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摘要 情境感知是智慧学习的必要条件,情境感知系统能够根据当前情境为用户提供合适的信息和服务,在情境式学习、个性化学习和资源推荐等领域有着非常广泛的应用。基于对情境与情境感知的概念剖析、特点分析及现有分类方式的分析,以学习资源推荐系统为例,提出情境信息建模方法,即通过情境相关实体的确定、实体情境信息的提炼、情境信息间关系的确定,形成情境信息描述模型;提出一种情境感知的系统框架,实现对情境信息的管理及高度共享。同时通过对当前推荐系统的推荐方式分析,详细阐述了不同实体的情境信息在资源推荐系统中的应用策略及适用的推荐方式。最后明确了该领域在基础数据集建设、情境的获取与共享、情境信息的标准化等有待进一步研究的问题。 Context awareness is one of the necessary conditions of smart learning. Context-aware systems can provide relevant information and services to users according to the context. These systems can be widely applied in situated learning, personalized learning, and resource recommendation. In this paper, using a learning resources recommendation system as an example, the authors first propose a context information modeling method based on the analyses of the concepts, the characteristics, and the classification of context and context-awareness. The authors then formulate a model that can describe context information through the methods of identifying information, and recognizing the relationships among the entity of context, refining the entity's context context information. The authors thus suggest a framework of context-aware system that helps to realize the management and share of context information across applications. On the analysis of the patterns of current recommendation systems, the authors also exhaustively describe the strategy and the appropriate recommendation method of using different entity context information in resource recommendation systems. Lastly, the authors discuss future research in terms of the construction of basic data set, the obtaining and sharing of context, the standardization of context information, and others.
出处 《电化教育研究》 CSSCI 北大核心 2016年第2期54-61,共8页 E-education Research
基金 教育部-英特尔信息技术专项科研基金"云服务模式下的教室与智能终端技术"(课题编号:MOE-INTEL-2012-05) 上海市科委技术委员会工程技术研究中心能力提升项目"上海数字化教育装备工程技术研究中心"(课题编号:13DZ2280300)
关键词 智慧学习 情境感知 推荐系统 学习资源 推荐策略 Smart Learning Context-awareness Recommendation System Learning Resources Recommendation Strategy
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