DATA MINING TECHNIQUES FOR EDUCATIONAL DATA: A REVIEW
| Main Authors: | Pragati Sharma, Dr. Sanjiv Sharma |
|---|---|
| Format: | Article Journal |
| Terbitan: |
, 2018
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/1202113 |
| ctrlnum |
1202113 |
|---|---|
| fullrecord |
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<dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><creator>Pragati Sharma</creator><creator>Dr. Sanjiv Sharma</creator><date>2018-02-28</date><description>Recently, data mining is gaining more popularity among researcher. Data mining provides various techniques and methods for analysing data produced by various applications of different domain. Similarly, Educational mining is providing a way for analyzing educational data set. Educational mining concerns with developing methods for discovering knowledge from data that come from educational field and it helps to extract the hidden patterns and to discover new knowledge from large educational databases with the use of data mining techniques and tools. Extracted knowledge from educational mining can be used for decision making in higher educational institutions. This paper is based on literature review of different data mining techniques along with certain algorithms like classification, clustering etc. This paper represents the effectiveness of mining techniques with educational data set for higher education institutions.</description><identifier>https://zenodo.org/record/1202113</identifier><identifier>10.5281/zenodo.1202113</identifier><identifier>oai:zenodo.org:1202113</identifier><relation>doi:10.5281/zenodo.1202112</relation><rights>info:eu-repo/semantics/openAccess</rights><rights>https://creativecommons.org/licenses/by/4.0/legalcode</rights><source>INTERNATIONAL JOURNAL OF ENGINEERING TECHNOLOGIES AND MANAGEMENT RESEARCH 5(2 :SE) 166-177</source><subject>Data mining; Educational Mining; Classification; Clustering.</subject><title>DATA MINING TECHNIQUES FOR EDUCATIONAL DATA: A REVIEW</title><type>Journal:Article</type><type>Journal:Article</type><recordID>1202113</recordID></dc>
|
| format |
Journal:Article Journal Journal:Journal |
| author |
Pragati Sharma Dr. Sanjiv Sharma |
| title |
DATA MINING TECHNIQUES FOR EDUCATIONAL DATA: A REVIEW |
| publishDate |
2018 |
| topic |
Data mining Educational Mining Classification Clustering |
| url |
https://zenodo.org/record/1202113 |
| contents |
Recently, data mining is gaining more popularity among researcher. Data mining provides various techniques and methods for analysing data produced by various applications of different domain. Similarly, Educational mining is providing a way for analyzing educational data set. Educational mining concerns with developing methods for discovering knowledge from data that come from educational field and it helps to extract the hidden patterns and to discover new knowledge from large educational databases with the use of data mining techniques and tools. Extracted knowledge from educational mining can be used for decision making in higher educational institutions. This paper is based on literature review of different data mining techniques along with certain algorithms like classification, clustering etc. This paper represents the effectiveness of mining techniques with educational data set for higher education institutions. |
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IOS16997.1202113 |
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ZAIN Publications |
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7213 |
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library:special library |
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Cognizance Journal of Multidisciplinary Studies |
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5267 |
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Cognizance Journal of Multidisciplinary Studies |
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16997 |
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Multidisciplinary |
| city |
Stockholm |
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INTERNASIONAL |
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1 |
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IOS16997 |
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