基于领域的电子学习相关资料推荐与检索

Aijuan Dong, Baoying Wang
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引用次数: 10

摘要

一个好的电子学习系统应该在最合适的时间和地点向学习者提供相关的学习材料,以促进学习者获取知识和技能。本文提出了基于领域的电子学习相关资料推荐和检索方法。因为相关性通常依赖于领域。在一个领域高度相关的材料可能在另一个领域无关,我们根据他们的领域对用户进行分组。根据内容,准备了多组相关文档,每个选择的领域对应一组。在搜索场景中,搜索站点是按域选择的,只对选择的相关站点进行搜索。为了证明我们的想法,我们以基因组与生物信息学虚拟会议为实验平台,开发了一个演示视频访问平台。其实现涉及图像和视频处理、数据库管理、编程和多媒体学习材料展示等技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Domain-Based Recommendation and Retrieval of Relevant Materials in E-learning
A good e-learning system should deliver relevant learning materials to learner at the most appropriate time and locations to facilitate learners' acquisition of knowledge and skills. In this paper, we propose domain-based recommendation and retrieval of relevant materials in e- learning. Since relevancy is often domain dependent. Materials that are highly related in one domain might be irrelevant in another domain, we group users by their domains. Based on the content, multiple sets of relevant documents, one for each chosen domain, are prepared. In a search scenario, search sites are selected by domain and search is performed on the chosen relevant sites only. To demonstrate our idea, we use Virtual Conference on Genomic and Bioinformatics as the test bed and develop a presentation video access platform. The implementation involves techniques in image and video processing, database management, programming, and multimedia learning materials presentation.
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