Association Rules Based Opinion Mining for E-Learning and Electronic Literature Reading

Shubham Dubey, Ispany Marton
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Abstract

The revolution in Information technology has transformed our academics and projected it in the new dimension. ICT supported learning is best facilitating learners’ needs. With some pros there are some cons as well which are affiliated with e-learning. This study is analyzing the opinions of respondents towards e-learning and electronic literature reading. To analyze the response authors employed Apriori algorithm of association rule mining approach. The support and confidence values or the analysis were kept high (≥85) to achieve good quality of association among such factors. Study finds stress generated while adopting e-learning and e-reading has higher association with content availability in web resources. This very inferable that the wide content range results more surfing and searching and resulting stress. Study also found that the distractions caused by resource divergence are strongly associated with stress and problems faced in eyes. The study is giving significant contribution towards policy making and analysis of factors that affects the learners’ choices and problems the most.
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基于关联规则的电子学习和电子文献阅读意见挖掘
信息技术革命改变了我们的学术,并将其投射到新的维度。信息通信技术支持的学习最能满足学习者的需求。有一些优点,也有一些缺点,这与电子学习有关。本研究旨在分析受访者对电子学习和电子文献阅读的看法。为了分析响应,作者采用关联规则挖掘方法中的Apriori算法。分析的支持度和置信度保持较高(≥85),以达到这些因素之间良好的关联质量。研究发现,采用电子学习和电子阅读时产生的压力与网络资源中的内容可用性有较高的相关性。这是非常可以推断的,广泛的内容范围导致更多的冲浪和搜索和由此产生的压力。研究还发现,由资源分散引起的分心与眼睛面临的压力和问题密切相关。该研究为政策制定和分析影响学习者选择的因素和问题做出了重要贡献。
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