数据挖掘和意见挖掘:教育背景下的工具

Myriam Peñafiel, Stefanie Vásquez, Diego Vásquez, Juan Zaldumbide, S. Luján-Mora
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引用次数: 5

摘要

使用网络作为一个通用的交流平台产生了大量的数据(大数据),在许多情况下,需要对这些数据进行处理,以便在面对怀疑这些信息可信度的怀疑论者时成为有用的知识。来自教育背景的网络数据的使用需要解决,因为大量的非结构化信息没有得到重视,失去了可以使用的有价值的信息。为了解决这个问题,我们提出使用情感分析等数据挖掘技术来验证来自教育平台的信息。本研究的目的是提出一种方法,允许用户以一种简单的方式应用情感分析,因为尽管一些研究人员已经这样做了,但很少有人在教育背景下使用数据。结果表明,该方法可以应用于类似的情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Mining and Opinion Mining: A Tool in Educational Context
The use of the web as a universal communication platform generates large volumes of data (Big data), which in many cases, need to be processed so that they can become useful knowledge in face of the sceptics who have doubts about the credibility of such information. The use of web data that comes from educational contexts needs to be addressed, since that large amount of unstructured information is not being valued, losing valuable information that can be used. To solve this problem, we propose the use of data mining techniques such as sentiment analysis to validate the information that comes from the educational platforms. The objective of this research is to propose a methodology that allows the user to apply sentiment analysis in a simple way, because although some researchers have done it, very few do with data in the educational context. The results obtained prove that the proposal can be used in similar cases.
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