• The Journal of Asian Finance, Economics and Business
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• v.7 no.2
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• pp.221-228
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• 2020

This study suggests an alternative to the conventional collaborative filtering method for predicting consumer choice, using case-based reasoning. The algorithm of case-based reasoning determines the similarity between the alternative sets that each subject chooses. Case-based reasoning uses the inverse of the normalized Euclidian distance as a similarity measurement. This normalized distance is calculated by the ratio of difference between each attribute level relative to the maximum range between the lowest and highest level. The alternative case-based reasoning based on similarity predicts a target subject's choice by applying the utility values of the subjects most similar to the target subject to calculate the utility of the profiles that the target subject chooses. This approach assumes that subjects who deliberate in a similar alternative set may have similar preferences for each attribute level in decision making. The result shows the similarity between comparable alternatives the consumers consider buying is a significant factor to predict the consumer choice. Also the interaction effect has a positive influence on the predictive accuracy. This implies the consumers who looked into the same alternatives can probably pick up the same product at the end. The suggested alternative requires fewer predictors than conjoint analysis for predicting customer choices.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.347-354
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• 1999

The credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this paper, we present a new approach to credit rating of customers based on the rough set theory. The concept of a rough set appeared to be an effective tool for the analysis of customer information systems representing knowledge gained by experience. The customer information system describes a set of customers by a set of multi-valued attributes, called condition attributes. The customers are classified into groups of risk subject to an expert's opinion, called decision attribute. A natural problem of knowledge analysis consists then in discovering relationships, in terms of decision rules, between description of customers by condition attributes and particular decisions. The rough set approach enables one to discover minimal subsets of condition attributes ensuring an acceptable quality of classification of the customers analyzed and to derive decision rules from the customer information system which can be used to support decisions about rating new customers. Using the rough set approach one analyses only facts hidden in data, it does not need any additional information about data and does not correct inconsistencies manifested in data; instead, rules produced are categorized into certain and possible. A real problem of the evaluation of the evaluation of credit rating by a department store is studied using the rough set approach.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.296-301
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• 1998

The Rough Set theory suggested by Pawlak in 1982 has been useful in AI, machine learning, knowledge acquisition, knowledge discovery from databases, expert system, inductive reasoning. etc. The main advantages of rough set are that it does not need any preliminary or additional information about data and reduce the superfluous informations. but it is a significant disadvantage in the real application that the inference result form is not the real control value but the divided disjoint interval attribute. In order to overcome this difficulty, we will propose approach in which Rough set theory and Neuro-fuzzy fusion are combined to obtain the optimal rule base from lots of input/output datum. These results are applied to the rule construction for infering the temperatures of refrigerator's specified points.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.3
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• pp.181-187
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• 2014

Dealing with uncertainty is always a challenging problem. Intuitionistic fuzzy sets was presented to manage situations in which experts have some membership and non-membership value to assess an alternative. Hesitant fuzzy sets was used to handle such situations in which experts hesitate between several possible membership values to assess an alternative. In this paper, the concept of intuitionistic hesitant fuzzy set is introduced to provide computational basis to manage the situations in which experts assess an alternative in possible membership values and non-membership values. Distance measure is defined between any two intuitionistic hesitant fuzzy elements. Fuzzy technique for order preference by similarity to ideal solution is developed for intuitionistic hesitant fuzzy set to solve multi-criteria decision making problem in group decision environment. An example is given to illustrate this technique.

• Journal of the Korean Institute of Landscape Architecture
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• v.28 no.1
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• pp.19-28
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• 2000

The purposes of this study are two folds: a) to introduce conjoint choice model to research the choice behavior of theme park users, and b) to suggest the strategies to strengthen the competitiveness of theme parks. The major four theme parks in Seoul metropolitan areas were selected as study areas. A leading polling agency was employed to select 432 respondents by probability sampling and to conduct face-to-face interview. Both alternative generating and choice set generating fractional factorial design were conducted simultaneously to meet the necessary and sufficient conditions for calibration of the conjoint choice model. Dummy coding was used to represent the attribute levels, and the alternative-specific model was calibrated. The goodness-of-fit of the model was quite satisfactory($\rho$$^2$=0.47950), and most parameters values had to expected sign and magnitude. Car was preferred transport mode to shuttle bus for visiting theme parks ; however the most ideal attribute levels only were estimated significantly. Most attribute levels of shuttle bus were estimated significantly except the Dream Land, which is the least attractive park among study areas. Simulation results showed that the shuttle bus was a mode worth providing to switch the current car dominant visiting pattern of theme parks, which will be one the effective strategies to attract more patrons, especially for potential users adjacent to parks. Several ideals were suggested for future researches, in terms of utilization of more general utility function and new base alternative, and inclusion of more salient attributes such as constraints in the model.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.247-256
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• 2016

This paper proposes Context-Awareness Healthcare for Disease Reasoning based on Fuzzy Logic. It consists of a Fuzzy-based Context-Awareness Module (FCAM) and a Fuzzy-based Disease Reasoning Module (FDRM). The FCAM computes a Correlation coefficient and Support between a Condition attribute and a Decision attribute and generates Fuzzy rules by using just the Condition attribute whose Correlation coefficient and Support are high. According to the result of accuracy experiment using a SIPINA mining tool, those generated by Fuzzy Rule based on Correlation coefficient and Support (FRCS) and Improved C4.5 are 0.84 and 0.81 each average. That is, compared to the Improved C4.5, the FRCS reduces the number of generated rules, and improves the accuracy of rules. In addition, the FDRM can not only reason a patient’s disease accurately by using the generated Fuzzy Rules and the patient disease information but also prevent a patient’s disease beforehand.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.232-241
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• 2000

This study suggests an integrated method based on concept hierarchies, information gain, and rough set theory for efficient discovery rules from a large amount of data, and implements an optimal rules discovery system. Our approach applies attribute-oriented concept ascension technique to extract generalized knowledge from a database, knowledge reduction technique to remove superfluous attributes and attribute values, and significance of attributes to induce optimal rules. The system first reduces the size of database by removing the duplicate tuples through the condition attributes which have no influences on the decision attributes, and finally induces simplified optimal rules by removing the superfluous attribute values by analyzing the dependency relationships among the attributes. And we induce some decision rules from actual data by using the system and test rules to new data, and evaluate that the rules are well suited to them.

• Journal of the Korean Institute of Plant Engineering
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• v.23 no.4
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• pp.65-75
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• 2018

Importance-Performance Analysis(IPA) holds the assumption that the degree of physical fulfilment of quality attributes and the satisfaction of that attribute is linear. Therefore, IPA can be applied to the traditional one-dimensional attributes, not to other quality elements such as attractive or must-be attributes. To overcome this problem, several articles introduced methods that integrate IPA into the concept of two-dimensional quality. However, these articles are rather conceptual focusing on the differentiation of quality attributes depend on quality elements in IPA. To provide empirical evidence of the dependent relationship between attribute importance and satisfaction in IPA, this study introduces a weighted importance approach and provides validation method using Bacon's priority model, a regression model. For this, the current research investigates 23 quality attributes of TV set for the results of Kano's model, which are adopted from Kim et al., and conducted a survey of 118 university students for the results of the importance/satisfaction and improvement priority. The result of the proposed approach shows better result than those using the conventional way, based on R-square of the regression model.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.648-651
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• 2013

클라우드 시스템에서는 데이터 소유자가 아닌 클라우드 서비스 제공자가 각 개인의 데이터에 대한 저장과 관리를 책임진다. 따라서 클라우드 서버 상의 사용자 데이터에 대한 보안을 보장해 주는 것이 가장 중요한 이슈이다. 데이터 보안 문제는 안전하고 효율적인 접근제어 기술을 통해 해결 할 수 있다. 기존 시스템에서 많이 이용되고 있는 RBAC(Role based access control)은 접근제어의 형태가 주로 수직적이고, 데이터 접근가능 여부를 역할이라는 고정적인 값에 따라 결정하기 때문에 동적인 클라우드 환경에 적합하지 않다. 반면 HASBE(Hierarchical attribute set based encryption) 모델은 ABAC(Attribute based access control)를 통해 유연하고 탄력적인 접근제어를 제공한다. 또한 HASBE 는 인가자(Authority)와 사용자의 관계 모델이 계층적인 구조를 갖고 있기 때문에 큰 조직에서 수많은 사용자들의 데이터 관리와 키 분배를 좀더 효율적으로 할 수 있다. 본 논문에서는 위의 계층적인 모델에서 더 나아가서, 실제 클라우드 환경에서 데이터가 가질 수 있는 복잡한 속성과 인가자의 관계를 고려해 다중 인가자의 개념이 더해진 모델을 제안한다.

• The Journal of Fisheries Business Administration
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• v.54 no.3
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• pp.17-28
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• 2023

In this study, a conjoint analysis was conducted to derive a combination of fishing quota management system by fish species preferred by fishermen. In the analysis, detailed levels were set according to each attribute of the system. For analysis, this study conducted a design question survey for conjoint analysis on 303 fishermen engaged in fishing activities in the offshore and coastal sea. The Conjoint analysis was conducted on all fishermen, offshore fishermen and coastal fishermen. In addition, an analysis was conducted on TAC system participants and non-TAC system participants, and the targets were classified for comparison according to the characteristics of fishermen. Fishermen's preference for the system confirmed for six attribute ("catching fish even if there is no fishing quota", "how to allocate fishing quota", "fishing quota management agency", "upper limit of fishing quota," "Possibility of Trading in the Fishing Quota", and "Application of Other Regulations.") and the detailed level of each attribute. As a result of the analysis of the importance of attributes, fishermen thought that "fishing quota management agency (24.1%)" was very important, and "catching fish even if there is no fishing quota (23.9%)" and "how to allocate fishing quotas (22.9%)" were also given some importance.