Exceptional Association Rule Set Discovery from Community-Dwelling Elderly People Database

Kaoru Shimada; Hisae Aoki; Keiko Kubota; Satoru Haresaku; Shinsuke Mizutani; Toru Naito; Michio Ueno

doi:10.1109/SMC.2018.00558

Exceptional Association Rule Set Discovery from Community-Dwelling Elderly People Database

Kaoru Shimada, Hisae Aoki, Keiko Kubota, Satoru Haresaku, Shinsuke Mizutani, Toru Naito, Michio Ueno

Department of Dental Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

An extended method to discover exceptional association rule sets from incomplete databases is proposed. In an exceptional rule set, each itemset X, Y has a weak or no statistical relation to class C; however, the join of X and Y has a strong relation to C. An exceptional rule set can be used to infer long rules for the join of X and Y and to discover rare rules. The proposed method calculates the rule evaluation odds ratio directly. In this study, the method is applied to rule discovery using a database of community-dwelling elderly. Experimental results demonstrate that the proposed method can help discover interesting rare rules and exceptional association rule sets. The results show the effectiveness of the proposed method in the fields of medicine and health care.

Original language	English
Title of host publication	Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3295-3300
Number of pages	6
ISBN (Electronic)	9781538666500
DOIs	https://doi.org/10.1109/SMC.2018.00558
Publication status	Published - Jan 16 2019
Event	2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 - Miyazaki, Japan Duration: Oct 7 2018 → Oct 10 2018

Publication series

Name	Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018

Conference

Conference	2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
Country/Territory	Japan
City	Miyazaki
Period	10/7/18 → 10/10/18

All Science Journal Classification (ASJC) codes

Information Systems
Information Systems and Management
Health Informatics
Artificial Intelligence
Computer Networks and Communications
Human-Computer Interaction

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/SMC.2018.00558

Cite this

Shimada, K., Aoki, H., Kubota, K., Haresaku, S., Mizutani, S., Naito, T., & Ueno, M. (2019). Exceptional Association Rule Set Discovery from Community-Dwelling Elderly People Database. In Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 (pp. 3295-3300). Article 8616555 (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2018.00558

Exceptional Association Rule Set Discovery from Community-Dwelling Elderly People Database. / Shimada, Kaoru; Aoki, Hisae; Kubota, Keiko et al.
Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018. Institute of Electrical and Electronics Engineers Inc., 2019. p. 3295-3300 8616555 (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Shimada, K, Aoki, H, Kubota, K, Haresaku, S, Mizutani, S, Naito, T & Ueno, M 2019, Exceptional Association Rule Set Discovery from Community-Dwelling Elderly People Database. in Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018., 8616555, Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, Institute of Electrical and Electronics Engineers Inc., pp. 3295-3300, 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, Miyazaki, Japan, 10/7/18. https://doi.org/10.1109/SMC.2018.00558

Shimada K, Aoki H, Kubota K, Haresaku S, Mizutani S, Naito T et al. Exceptional Association Rule Set Discovery from Community-Dwelling Elderly People Database. In Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 3295-3300. 8616555. (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018). doi: 10.1109/SMC.2018.00558

Shimada, Kaoru ; Aoki, Hisae ; Kubota, Keiko et al. / Exceptional Association Rule Set Discovery from Community-Dwelling Elderly People Database. Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 3295-3300 (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018).

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abstract = "An extended method to discover exceptional association rule sets from incomplete databases is proposed. In an exceptional rule set, each itemset X, Y has a weak or no statistical relation to class C; however, the join of X and Y has a strong relation to C. An exceptional rule set can be used to infer long rules for the join of X and Y and to discover rare rules. The proposed method calculates the rule evaluation odds ratio directly. In this study, the method is applied to rule discovery using a database of community-dwelling elderly. Experimental results demonstrate that the proposed method can help discover interesting rare rules and exceptional association rule sets. The results show the effectiveness of the proposed method in the fields of medicine and health care.",

author = "Kaoru Shimada and Hisae Aoki and Keiko Kubota and Satoru Haresaku and Shinsuke Mizutani and Toru Naito and Michio Ueno",

note = "Funding Information: This work was partly supported by JSPS KAKENHI Grant Number 16K00316. Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 ; Conference date: 07-10-2018 Through 10-10-2018",

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AU - Shimada, Kaoru

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AU - Kubota, Keiko

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AU - Mizutani, Shinsuke

AU - Naito, Toru

AU - Ueno, Michio

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AB - An extended method to discover exceptional association rule sets from incomplete databases is proposed. In an exceptional rule set, each itemset X, Y has a weak or no statistical relation to class C; however, the join of X and Y has a strong relation to C. An exceptional rule set can be used to infer long rules for the join of X and Y and to discover rare rules. The proposed method calculates the rule evaluation odds ratio directly. In this study, the method is applied to rule discovery using a database of community-dwelling elderly. Experimental results demonstrate that the proposed method can help discover interesting rare rules and exceptional association rule sets. The results show the effectiveness of the proposed method in the fields of medicine and health care.

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Exceptional Association Rule Set Discovery from Community-Dwelling Elderly People Database

Abstract

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All Science Journal Classification (ASJC) codes

UN SDGs

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