Mining Least Association Rules of Degree Level Programs Selected by Students
One of the most popular and important studies in data mining is association rules mining. Generally, association rules can be divided into two categories called frequent and least. However, finding the least association rules is more complex and time consuming as compared to the frequent one. These...
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| Format: | Article |
| Language: | en |
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SERSC
2014
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| Online Access: | http://umpir.ump.edu.my/id/eprint/3787/1/2013-maseri_Mining_Least.pdf http://umpir.ump.edu.my/id/eprint/3787/ http://www.sersc.org/journals/IJMUE/vol9_no1_2014/23.pdf |
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| author | Zailani, Abdullah Herawan, Tutut Noraziah, Ahmad Mustafa, Mat Deris |
| author_facet | Zailani, Abdullah Herawan, Tutut Noraziah, Ahmad Mustafa, Mat Deris |
| author_sort | Zailani, Abdullah |
| building | UMPSA Library |
| collection | Institutional Repository |
| content_provider | Universiti Malaysia Pahang Al-Sultan Abdullah |
| content_source | UMPSA Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | One of the most popular and important studies in data mining is association rules mining. Generally, association rules can be divided into two categories called frequent and least. However, finding the least association rules is more complex and time consuming as compared to the frequent one. These rules are very useful in certain application domain such as determining the exceptional association between university’s programs being selected by students. Therefore in this paper, we apply our novel measure called Definite Factors (DF) to determine the significant least association rules from undergraduate’s program selection database. The dataset of computer science student for July 2008/2009 intake from Universiti Malaysia Terengganu was employed in the experiment. The result shows that our measurement can mine these rules and it is at par with the existing benchmarked Relative Support Apriori (RSA) measurement. |
| format | Article |
| id | my.ump.umpir.3787 |
| institution | Universiti Malaysia Pahang |
| language | en |
| publishDate | 2014 |
| publisher | SERSC |
| record_format | eprints |
| spelling | my.ump.umpir.37872017-08-15T04:39:26Z http://umpir.ump.edu.my/id/eprint/3787/ Mining Least Association Rules of Degree Level Programs Selected by Students Zailani, Abdullah Herawan, Tutut Noraziah, Ahmad Mustafa, Mat Deris QA76 Computer software One of the most popular and important studies in data mining is association rules mining. Generally, association rules can be divided into two categories called frequent and least. However, finding the least association rules is more complex and time consuming as compared to the frequent one. These rules are very useful in certain application domain such as determining the exceptional association between university’s programs being selected by students. Therefore in this paper, we apply our novel measure called Definite Factors (DF) to determine the significant least association rules from undergraduate’s program selection database. The dataset of computer science student for July 2008/2009 intake from Universiti Malaysia Terengganu was employed in the experiment. The result shows that our measurement can mine these rules and it is at par with the existing benchmarked Relative Support Apriori (RSA) measurement. SERSC 2014 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/3787/1/2013-maseri_Mining_Least.pdf Zailani, Abdullah and Herawan, Tutut and Noraziah, Ahmad and Mustafa, Mat Deris (2014) Mining Least Association Rules of Degree Level Programs Selected by Students. International Journal of Multimedia and Ubiquitous Engineering (IJMUE), 9 (1). pp. 241-254. ISSN 1975-0080. (Published) http://www.sersc.org/journals/IJMUE/vol9_no1_2014/23.pdf |
| spellingShingle | QA76 Computer software Zailani, Abdullah Herawan, Tutut Noraziah, Ahmad Mustafa, Mat Deris Mining Least Association Rules of Degree Level Programs Selected by Students |
| title | Mining Least Association Rules of Degree Level Programs Selected by Students |
| title_full | Mining Least Association Rules of Degree Level Programs Selected by Students |
| title_fullStr | Mining Least Association Rules of Degree Level Programs Selected by Students |
| title_full_unstemmed | Mining Least Association Rules of Degree Level Programs Selected by Students |
| title_short | Mining Least Association Rules of Degree Level Programs Selected by Students |
| title_sort | mining least association rules of degree level programs selected by students |
| topic | QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/3787/1/2013-maseri_Mining_Least.pdf http://umpir.ump.edu.my/id/eprint/3787/ http://www.sersc.org/journals/IJMUE/vol9_no1_2014/23.pdf |
| url_provider | http://umpir.ump.edu.my/ |