| 试论社区数字学习个性化服务的必要性与设计思路 |
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| 引用本文： | 邵念兵.试论社区数字学习个性化服务的必要性与设计思路[J].河南广播电视大学学报,2014(4):1-5. |
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| 作者姓名： | 邵念兵 |
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| 作者单位： | 江苏电大昆山学院,江苏昆山215300 |
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| 摘 要： | 目前我国社区数字化学习的平台建设和服务发展迅速,这一方面有助于拓展市民学习空间,为其提供更加开放、便捷、共享的学习机会。另一方面由于重硬件轻软件、重宣传轻互动、重自建轻共享等错误观念,导致数字化学习难以满足广大学员实际的学习需求,学习效果和影响均不如预期。为此,本文提出社区数字化学习的服务方式要体现以人为本,力求大众化、个性化,具体表现为个性化的资源搜索、个性化的资源推荐、个性化的资源导航、个性化的资源共享等内容,并对其中比较基本的个性化资源搜索问题进行了进一步分析。根据现有搜索技术的原理和特点,提出了内容过滤与协作过滤相结合的个性化搜索服务的设计思路和关键技术。
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| 关 键 词： | 个性化 数字化学习 用户模型 信息过滤 |
Analysis on the Necessity and Design Thought of Personalized Service of Community Digital Learning |
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| Shao Nianbing.Analysis on the Necessity and Design Thought of Personalized Service of Community Digital Learning[J].Journal of Henan Radio & TV University,2014(4):1-5. |
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| Authors: | Shao Nianbing |
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| Institution: | Shao Nianbing (Jiangsu Radio＆TV University, Kunshan, Jiangsu, 215300) |
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| Abstract: | Currently the platform construction and service of community digital learning have been developing rapidly. On the one hand, it helps to develop the citizens＇ learning space and provides more open, convenient and shared learning opportunities. On the other hand, because of the wrong concepts such as emphasizing hardware and despising software, emphasizing publicity and despising interaction, emphasizing self-built and despising sharing and so on, the digital learning can not meet the actual learning demands of students, and the learning effects and learning influence can not as well as expected. Hence, the paper proposes that the service pattern of community digital learning should reflect people oriented, strive to popularization and personalization whose concrete performance are personalized resource search, personalized resource recommend, personalized resource guide, personalized resource sharing and so on, and further analyzes the personalized resource search which is the most basic among the above. According to the principles and features of existing searching technologies, this paper puts forward to the design thoughts and key technologies of personalized searching service which are the combination of content filtering and collaborative filtering. |
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| Keywords: | personalization digital learning user mode information filtering |
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