大数据分析

P. Guleria, M. Sood
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引用次数: 1

摘要

由于数字交易和数据源数量的增加,每次交互都会产生大量的非结构化数据。在这种情况下,数据挖掘的概念具有重要意义,因为可以从大量数据中检索有用的信息/趋势/预测,称为大数据。大数据预测分析正在大举进军教育领域,因为随着新技术的采用,新的学术趋势正在被引入教育系统。不同种类的大数据的积累,对学习者和教育机构如何通过提高战略/业务决策能力来保证教育质量提出了新的挑战。因此,作者通过提出一个支持系统来解决这个问题,该系统可以指导学生根据他们的个人喜好选择并专注于正确的课程。本章为读者提供了有关教育框架和相关数据挖掘的必要信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big Data Analytics
Due to an increase in the number of digital transactions and data sources, a huge amount of unstructured data is generated by every interaction. In such a scenario, the concepts of data mining assume great significance as useful information/trends/predictions can be retrieved from this large amount of data, known as big data. Big data predictive analytics are making big inroads into the educational field because with the adoption of new technologies, new academic trends are being introduced into educational systems. This accumulation of large data of different varieties throws a new set of challenges to the learners as well as educational institutions in ensuring the quality of their education by improving strategic/operational decision-making capabilities. Therefore, the authors address this issue by proposing a support system that can guide the student to choose and to focus on the right course(s) based on their personal preferences. This chapter provides the readers with the requisite information about educational frameworks and related data mining.
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