공용환경 설계를 위한 선호도 기반 클러스터링 (Preference‐based Clustering for Intelligent Shared Environments)

서지정보

· 발행기관 : 한국산업경영시스템학회
· 수록지 정보 : 한국산업경영시스템학회지 / 36권 / 1호 / 64 ~ 69페이지
· 저자명 : 손기혁, 옥창수

초록

In ubiquitous computing, shared environments adjust themselves so that all users in the environments are satisfied as possible.
Inevitably, some of users sacrifice their satisfactions while the shared environments maximize the sum of all users’ satisfactions.
In our previous work, we have proposed social welfare functions to avoid a situation which some users in the system face the worst setting of environments. In this work, we consider a more direct approach which is a preference based clustering to handle this issue. In this approach, first, we categorize all users into several subgroups in which users have similar tastes to environmental parameters based on their preference information. Second, we assign the subgroups into different time or space of the shared environments. Finally, each shared environments can be adjusted to maximize satisfactions of each subgroup and consequently the optimal of overall system can be achieved. We demonstrate the effectiveness of our approach with a numerical analysis.

영어초록

In ubiquitous computing, shared environments adjust themselves so that all users in the environments are satisfied as possible.
Inevitably, some of users sacrifice their satisfactions while the shared environments maximize the sum of all users’ satisfactions.
In our previous work, we have proposed social welfare functions to avoid a situation which some users in the system face the worst setting of environments. In this work, we consider a more direct approach which is a preference based clustering to handle this issue. In this approach, first, we categorize all users into several subgroups in which users have similar tastes to environmental parameters based on their preference information. Second, we assign the subgroups into different time or space of the shared environments. Finally, each shared environments can be adjusted to maximize satisfactions of each subgroup and consequently the optimal of overall system can be achieved. We demonstrate the effectiveness of our approach with a numerical analysis.

참고자료

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