Abstract
Recently, mining least association rule from the sequential data becomes more important in certain domain areas such as education, healthcare, text mining, etc. due to its uniqueness and usefulness. However, discovering such rule is a great challenge because it involves with a set of least items which usually holds a very low in term of support. Therefore, in this paper propose a model for mining sequential least association rule (2M-SELAR) that embedded with SELAR algorithm, and Critical Relative Support (CRS) and Definite Factor (DF) measures. The experimental results reveal that 2M-SELAR can successfully generate the desired rule from the given datasets.
Original language | English |
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Title of host publication | Proceedings of the International Conference on Data Engineering, DaEng 2015 |
Editors | Jemal H. Abawajy, Mohamed Othman, Rozaida Ghazali, Mustafa Mat Deris, Hairulnizam Mahdin, Tutut Herawan |
Publisher | Springer Verlag |
Pages | 91-99 |
Number of pages | 9 |
ISBN (Print) | 9789811317972 |
DOIs | |
Publication status | Published - 1 Jan 2019 |
Event | 2nd International Conference on Advanced Data and Information Engineering, DaEng 2015 - Bali, Indonesia Duration: 25 Apr 2015 → 26 Apr 2015 |
Publication series
Name | Lecture Notes in Electrical Engineering |
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Volume | 520 |
ISSN (Print) | 1876-1100 |
ISSN (Electronic) | 1876-1119 |
Conference
Conference | 2nd International Conference on Advanced Data and Information Engineering, DaEng 2015 |
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Country | Indonesia |
City | Bali |
Period | 25/4/15 → 26/4/15 |
Fingerprint
Keywords
- Data mining
- Education
- Sequential least association rules
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
Cite this
2M-SELAR : A Model for Mining Sequential Least Association Rules. / Abdullah, Zailani; Adam, Omer; Herawan, Tutut; Noraziah, Ahmad; Saman, Md Yazid Mohd; Hamdan, Abdul Razak.
Proceedings of the International Conference on Data Engineering, DaEng 2015. ed. / Jemal H. Abawajy; Mohamed Othman; Rozaida Ghazali; Mustafa Mat Deris; Hairulnizam Mahdin; Tutut Herawan. Springer Verlag, 2019. p. 91-99 (Lecture Notes in Electrical Engineering; Vol. 520).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - 2M-SELAR
T2 - A Model for Mining Sequential Least Association Rules
AU - Abdullah, Zailani
AU - Adam, Omer
AU - Herawan, Tutut
AU - Noraziah, Ahmad
AU - Saman, Md Yazid Mohd
AU - Hamdan, Abdul Razak
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Recently, mining least association rule from the sequential data becomes more important in certain domain areas such as education, healthcare, text mining, etc. due to its uniqueness and usefulness. However, discovering such rule is a great challenge because it involves with a set of least items which usually holds a very low in term of support. Therefore, in this paper propose a model for mining sequential least association rule (2M-SELAR) that embedded with SELAR algorithm, and Critical Relative Support (CRS) and Definite Factor (DF) measures. The experimental results reveal that 2M-SELAR can successfully generate the desired rule from the given datasets.
AB - Recently, mining least association rule from the sequential data becomes more important in certain domain areas such as education, healthcare, text mining, etc. due to its uniqueness and usefulness. However, discovering such rule is a great challenge because it involves with a set of least items which usually holds a very low in term of support. Therefore, in this paper propose a model for mining sequential least association rule (2M-SELAR) that embedded with SELAR algorithm, and Critical Relative Support (CRS) and Definite Factor (DF) measures. The experimental results reveal that 2M-SELAR can successfully generate the desired rule from the given datasets.
KW - Data mining
KW - Education
KW - Sequential least association rules
UR - http://www.scopus.com/inward/record.url?scp=85071429455&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85071429455&partnerID=8YFLogxK
U2 - 10.1007/978-981-13-1799-6_10
DO - 10.1007/978-981-13-1799-6_10
M3 - Conference contribution
AN - SCOPUS:85071429455
SN - 9789811317972
T3 - Lecture Notes in Electrical Engineering
SP - 91
EP - 99
BT - Proceedings of the International Conference on Data Engineering, DaEng 2015
A2 - Abawajy, Jemal H.
A2 - Othman, Mohamed
A2 - Ghazali, Rozaida
A2 - Deris, Mustafa Mat
A2 - Mahdin, Hairulnizam
A2 - Herawan, Tutut
PB - Springer Verlag
ER -