A Brief Analysis of Data Mining Techniques

Ali, Faraaz; Bhatt, Dhowmya; Choudhury, Tanupriya; Thakral, Abha

doi:10.1109/iccike47802.2019.9004252

Cited by 4 publications

(2 citation statements)

References 9 publications

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“…and post-processing. An important part of the DM process is the transformation of raw data (information that has not been analysed) into useful information (knowledge) [44]. The steps of the data mining process for extracting knowledge are shown in figure 1.…”

Section: Edm Processmentioning

confidence: 99%

Handling Big Data in Education: A Review of Educational Data Mining Techniques for Specific Educational Problems

Ampadu

2023

ACRT

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In the era of big data, where the amount of information is growing exponentially, the importance of data mining has never been greater. Educational institutions today collect and store vast amounts of data, such as student enrollment and attendance records, and their exam results. With the need to sift through enormous amounts of data and present it in a way that anyone can understand, educational institutions are at the forefront of this trend, and this calls for a more sophisticated set of algorithms. Data mining in education was born as a response to this problem. Traditional data mining methods cannot be directly applied to educational problems because of the special purpose and function they serve. Defining at-risk students, identifying priority learning requirements for varied groups of students, increasing graduation rates, monitoring institutional performance efficiently, managing campus resources, and optimizing curriculum renewal are just a few of the applications of educational data mining. This paper reviews methodologies used as knowledge extractors to tackle specific education challenges from large data sets of higher education institutions to the benefit of all educational stakeholders.

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Section: Edm Processmentioning

confidence: 99%

Handling Big Data in Education: A Review of Educational Data Mining Techniques for Specific Educational Problems

Ampadu

2023

ACRT

View full text Add to dashboard Cite

show abstract

“…The data mining process consists of phases that allow us to convert unknown information (raw data) into valid and meaningful information (knowledge) [24]. The following Fig.…”

Section: Data Mining Processmentioning

confidence: 99%