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首页> 外文会议>2012 6th International Conference on New Trends in Information Science, Service Science and Data Mining >A personalized recommendation system in E-Learning environment based on semantic analysis
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A personalized recommendation system in E-Learning environment based on semantic analysis

机译：基于语义分析的在线学习环境个性化推荐系统

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摘要

The proposal of various electronic learning contents, e.g. remote education or virtual classrooms, has given a powerful impetus to the E-Learning techniques. However, there still remain several hard and complicated problems unsolved. Especially when compared with e-commerce and medicine, the problems of the recommenders in E-Learning system have not been fully figured out. In this paper, a novel personalized semantic recommendation system (PSRS) for E-Learning is designed. The proposed PSRS system employs the Video Structurized Description (VSD) technique to extract the initial keywords description of the learning contents, and then adopts the lexical parsing technique to refine the descriptive words with a standard format according to the initial keywords. Subsequently, the PSRS adopts rules auto-updating (RAU) to automatically add sequential items into ontology rules. Depending on the specific ontology knowledge with domain rules, semantic mapping and intelligent reasoning techniques are applied to generate certain semantic related recommending items for the active learners. Experimental results indicate that the proposed PSRS preforms better in accuracy than any other existing algorithms.
机译：各种电子学习内容的建议，例如远程教育或虚拟教室，为电子学习技术提供了强大的动力。但是，仍然存在一些悬而未决的难题。特别是当与电子商务和医学相比时，电子学习系统中推荐者的问题还没有得到完全解决。本文设计了一种新颖的用于电子学习的个性化语义推荐系统（PSRS）。提出的PSRS系统采用视频结构化描述（VSD）技术提取学习内容的初始关键词描述，然后采用词法分析技术根据初始关键词对描述性词进行标准化。随后，PSRS采用规则自动更新（RAU）将顺序项自动添加到本体规则中。根据具有领域规则的特定本体知识，应用语义映射和智能推理技术为活跃学习者生成某些与语义相关的推荐项。实验结果表明，所提出的PSRS的预成型精度优于任何其他现有算法。

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