Classification of objective interestingness measures

Lan Phuong Phan; Nghia Quoc Phan; Vinh Cong Phan; Hung Huu Huynh; Hiep Xuan Huynh; Fabrice Guillet

Research Article

Classification of objective interestingness measures

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@ARTICLE{10.4108/eai.12-9-2016.151678,
    author={Lan Phuong Phan and Nghia Quoc Phan and Vinh Cong Phan and Hung Huu Huynh and Hiep Xuan Huynh and Fabrice Guillet},
    title={Classification of objective interestingness measures},
    journal={EAI Endorsed Transactions on Context-aware Systems and Applications},
    volume={3},
    number={10},
    publisher={EAI},
    journal_a={CASA},
    year={2016},
    month={9},
    keywords={objective interestingness measures, classification, property/criterion of interestingness measures, association rules.},
    doi={10.4108/eai.12-9-2016.151678}
}

Lan Phuong Phan
Nghia Quoc Phan
Vinh Cong Phan
Hung Huu Huynh
Hiep Xuan Huynh
Fabrice Guillet
Year: 2016
Classification of objective interestingness measures
CASA
EAI
DOI: 10.4108/eai.12-9-2016.151678

Lan Phuong Phan¹^,*, Nghia Quoc Phan², Vinh Cong Phan³, Hung Huu Huynh⁴, Hiep Xuan Huynh¹, Fabrice Guillet⁵

1: Can Tho University, Campus 2- 3/2 Street, Ninh Kieu District, Can Tho City, Vietnam
2: Tra Vinh University, No. 126 National Road 53, Ward 5, Tra Vinh City, Vietnam
3: Nguyen Tat Thanh University, 300A Nguyen Tat Thanh Street, Ward 13, District 4, Ho Chi Minh City, Vietnam
4: VNUK Institute for Research and Executive Education, The University of Danang, 41 Le Duan Street, Hai Chau District, Danang city, Vietnam
5: Polytech Nantes, University of Nantes, La Chantrerie rue Christian Pauc BP 50609 F-44306 Nantes Cedex 3, France

*Contact email: pplan@ctu.edu.vn

Abstract

The creation of the interestingness measures for evaluating the quality of the association rule - based knowledge plays an important role in the post-processing of the Knowledge Discovery from Databases. More and more interestingness measures are proposed by two approaches (subjective assessment and objective assessment), studying the properties or the attributes of the interestingness measures is important in understanding the nature of the objective interestingness measures. In this paper, we focus primarily on the objective interestingness measures to obtain a general view of recent researches on the nature of the objective interestingness measures, as well as complete a new classification on 109 selected objective interestingness measures on 6 criterions (independence, equilibrium, symmetry, variation, description, and statistics).

Keywords: objective interestingness measures, classification, property/criterion of interestingness measures, association rules.

Received: 2016-04-19
Accepted: 2016-07-14
Published: 2016-09-12
Publisher: EAI

: http://dx.doi.org/10.4108/eai.12-9-2016.151678

Copyright © 2016 Lan Phuong Phan et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.