• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 1997.11a
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• pp.484-491
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• 1997

In this paper, an approach to determine the in-ordinal condition of a room, which is based on multi variable analysis, is proposed. According to this approach, the distance of a state from the ordinal condition is thought to be evaluated by the Mahalanobis' distance. The temperature changes of a room were measured and their statistical characteristics such as distribution type, the mean value and the standard deviation are studied. The applicability of the method for the fire detection is also investigated.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.735-736
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• 2021

인터넷에서 댓글 시스템은 자신의 의사표현을 위한 시스템으로 널리 사용되고 있다. 하지만 이를 악용하여 상대방에 대한 혐오를 드러내기도 한다. 악성댓글에 대한 적절한 대처를 위해 빠르고 정확한 탐지는 필수적이다. 본 연구에서는 악성 댓글 분류 문제를 해결하기 위해서 순서가 있는 분류 레이블의 성질을 활용한 순서형 회귀 (Ordinal regression) 기반의 분류 모델을 제안한다. 일반적인 분류 모형과는 달리 혐오 발언 정도에 따라 다중 레이블을 부여하여 학습을 진행하였다. 실험을 통해 Korean Hate Speech Dataset에 대해 LSTM기반의 모형의 출력층을 다르게 구성하여 순서형 회귀 기반의 모형들의 성능을 비교하였다. 결과적으로 예측 결과에 대한 조율이 가능한 순서형 회귀 모형이 일반적인 순서형 회귀 모형에 비해서 편향된 예측에 대해 추가적인 성능 향상을 보였다.

• 한국데이터정보과학회:학술대회논문집
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• 2003.10a
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• pp.197-213
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• 2003

One of the well-studied problems in data mining is the search for association rules. The goal of association rule mining is to find all the rules with support and confidence exceeding some user specified thresholds. In this paper we consider the relation between the measure of association and the criteria of association rule for ordinal data.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.95-105
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• 2004

The main characteristic of the ordinal scale is that its categories have a logically or continuously ordered relationship to each other. A continuous type permits measuring degrees of differences among categories. Also, the specific amount of differences is important. In this paper we consider the scoring method using a dummy variable based on distance among categories.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.597-607
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• 2004

The primary interest of drug development studies is identifying the lowest dose level producing a desirable effect over that of the zero-dose control, which is referred as the minimum effective dose (MED). In this paper, we suggest a nonparametric procedure for identifying the MED with binary or ordered categorical response data. Proposed test and Williams' test are compared by Monte Carlo simulation study and discussed.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.576-584
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• 2006

Content-based video matching is measuring a similarity of video signature compared to the original clip and copies of media. Specially, it is very important to match the exact frame position, but it depends on frame rate, noise condition and compression format of video. Ordinal signature shows good performance than other video signatures under normal condition but the previous didn't try to find the uniqueness and robustness. Hua et al. performed a uniqueness test under compressed in different formats or frame size. However, they used other compression format image instead of noise in robustness test. This paper proposes robustness test method using several noise models and analyzes the performance of robustness and uniqueness.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.667-673
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• 2009

This paper presents an efficient facial expression recognition method by measuring the histogram distance based on preprocessing. The preprocessing that uses both centroid shift and histogram equalization is applied to improve the recognition performance, The distance measurement is also applied to estimate the similarity between the facial expressions. The centroid shift based on the first moment balance technique is applied not only to obtain the robust recognition with respect to position or size variations but also to reduce the distance measurement load by excluding the background in the recognition. Histogram equalization is used for robustly recognizing the poor contrast of the images due to light intensity. The proposed method has been applied for recognizing 72 facial expression images(4 persons * 18 scenes) of 320*243 pixels. Three distances such as city-block, Euclidean, and ordinal are used as a similarity measure between histograms. The experimental results show that the proposed method has superior recognition performances compared with the method without preprocessing. The ordinal distance shows superior recognition performances over city-block and Euclidean distances, respectively.

• Journal of the East Asian Society of Dietary Life
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• v.18 no.2
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• pp.165-171
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• 2008

The purpose of this study was to measure tourists' preference for alternative restaurants with different combinations of attribute levels: grown area logo, origin description, traditional food, fusion food, national food, and price. A total of 210 questionnaires were completed. A conjoint experimental method was used to develop hypothetical restaurants, and an ordinal probit model was used to measure the effects of the attribute levels on tourists' preference. The ordinal probit model analysis results for the data indicated an excellent model fit. The effects of the attribute levels on tourists' preferences were statistically significant. As expected, estimates of the marginal willingness to pay were statistically significant Moreover, the tourists were more willing to pay for grown area logo as compared to the other attribute levels. The tourists also considered the grown area logo as a very important attribute. Withe regard to developing and testing conjoint models in the design of choice experiments involving multifactor alternatives, this study may approach a deeper understanding of the conjoint experiment. Greater understanding of the conjoint experiment can improve the managerial diagnoses of the problems as well as the opportunities for different marketing strategies including local branding programs and menu development and marketing communications.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.161-176
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• 2005

In a situation that ordinal preferences on multiattribute weights are captured, we present two solution approaches: an exact approach and an approximate method. The former, an exact solution approach via interaction with a decision-maker, pursues the progressive reduction of a set of non-dominated alternatives by narrowing down the feasible attribute weights region. Subsequent interactive questions and responses, however, sometimes may not guarantee the best alternative or a complete rank order of a set of alternatives that the decision-maker desires to have. Approximate solution approaches, on the other hand, can be divided into three categories including surrogate weights methods, dominance value-based decision rules, and three classical decision rules. Their efficacies are evaluated in terms of choice accuracy via a simulation analysis. The simulation results indicate that a proposed hybrid approach, intended to combine an exact solution approach through interaction and a dominance value-based approach, is recommendable for aiding a decision making in a case that a final choice is seldom made at single step under attribute weights that are imprecisely specified beyond ordinal descriptions.

• Culinary science and hospitality research
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• v.14 no.2
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• pp.215-224
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• 2008

The objective for this research was to clarify the preference for alternative restaurants with different combinations of factor levels: local specialty food, non-local specialty food, very attentive service, moderately attentive service, not attentive service, traditional decoration, modern decoration, \10,000, \15,000, and \20,000. Total 230 copies of questionnaire were completed. Conjoint experiment method was used to develop full restaurant profiles. Ordinal probit model was used to measure the effects of factor levels on the preference. Results of the study demonstrated that the ordinal probit model analysis result for the data also indicated a good model fit. The effects of factor levels on the preference were statistically significant. As expected, the estimates of implicit price to pay were statistically significant. Moreover, the customers were more willing to pay for local specialty than other factor levels. The customers also considered the food factor as a very important factor. This research suggested that the customer's decision-making process for restaurants was best modeled as a conjoint experiment method that combines various factor levels. And it showed the results could be used as good data for understanding the relationships between the factors and preference in choosing food and restaurants in tourist areas.