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RSS-based e-learning recommendations exploiting fuzzy FCA for Knowledge Modeling

机译：基于RSS的电子学习建议，利用模糊FCA进行知识建模

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摘要

Nowadays, Web 2.0 focuses on user generated content, data sharing and collaboration activities. Formats like Really Simple Syndication (RSS) provide structured Web information, display changes in summary form and stay updated about news headlines of interest. This trend has also affected the e-learning domain, where RSS feeds demand for dynamic learning activities, enabling learners and teachers to access to new blog posts, to keep track of new shared media, to consult Learning Objects which meet their needs. This paper presents an approach to enrich personalized e-learning experiences with user-generated content, through a contextualized RSS-feeds fruition. The synergic exploitation of Knowledge Modeling and Formal Concept Analysis techniques enables the design and development of a system that supports learners in their learning activities by collecting, conceptualizing, classifying and providing updated information on specific topics coming from relevant information sources. An agent-based layer supervises the extraction and filtering of RSS feeds whose topics cover a specific educational domain.
机译：如今，Web 2.0专注于用户生成的内容，数据共享和协作活动。诸如Really Simple Syndication（RSS）之类的格式提供结构化的Web信息，以摘要形式显示更改，并保持有关感兴趣的新闻标题的最新信息。这种趋势也影响了电子学习领域，RSS满足了对动态学习活动的需求，使学习者和教师可以访问新的博客文章，跟踪新的共享媒体，咨询满足其需求的学习对象。本文提出了一种通过上下文相关的RSS提要成果来丰富用户生成的内容的个性化电子学习体验的方法。知识建模和形式概念分析技术的协同开发使系统的设计和开发成为可能，该系统通过收集，概念化，分类和提供来自相关信息源的特定主题的更新信息来支持学习者的学习活动。基于代理的层监督RSS提要的提取和过滤，其主题涉及特定的教育领域。

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