• Title/Summary/Keyword: Conditional Value

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Active Learning과 군집화를 이용한 고정키어구 추출 (Keyphrase Extraction Using Active Learning and Clustering)

  • 이현우;차정원
    • 대한음성학회지:말소리
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    • 제66호
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    • pp.87-103
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    • 2008
  • We describe a new active learning method in conditional random fields (CRFs) framework for keyphrase extraction. To save elaboration in annotation, we use diversity and representative measure. We select high diversity training candidates by sentence confidence value. We also select high representative candidates by clustering the part-of-speech patterns of contexts. In the experiments using dialog corpus, our method achieves 86.80% and saves 88% training corpus compared with those of supervised method. From the results of experiment, we can see that the proposed method shows improved performance over the previous methods. Additionally, the proposed method can be applied to other applications easily since its implementation is independent on applications.

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서울시내와 근교에 위치한 당일여가용 Recreation시설의 선택행동 확정에 관한 연구 : Generalized Logit Model의 적용 (Destination Choice Behavior for Recreation Areas : Application of Generalized Logit Models)

  • 홍성권
    • 한국조경학회지
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    • 제22권3호
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    • pp.1-12
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    • 1994
  • This study was carried out to identify destination choice behavior for one-day use recreation areas. Previous positioning study was utilized to select 4 study areas, and the secondary data were used for logit analyses. The Hausamn-McFadden test for IIA was conducted to examine whether conditional logit models are valid methodology for this study. The results revealed that IIA assumption among the study areas was violated; therefore, generalized binomial and generalized multinomial logit models were used in this study. In the binomial logit analysis, 2 to 5 independent variables were included in the models: their $\rho$2 values were from 0.1to 0.323, and accuracy of predictions were from 65.38 to 79.86 percent. In the multinomial logit analysis, 4 independent variables were included in the model: its $\rho$2 value was 0.207, and accuracy of prediction was 45.82 percent. The results showed that the conditional logit should be used with caution because of the IIA assumption. Several suggestions were described, mainly due to utilization of the secondary data for this study.

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퍼지-조건부확률을 이용한 전자상거래 검색 에이전트 모델에 관한 연구 (A Study on Electronic Commerce Navigation Agent Model Using Fuzzy-Conditional Probability)

  • 김명순
    • 한국컴퓨터정보학회논문지
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    • 제9권2호
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    • pp.1-6
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    • 2004
  • 기존의 전자상거래시스템 검색 에이전트들은 고객이 상품 검색을 위해 사용할 수 있는 질의어에 대해 매우 제한적으로 동작해왔다. 본 논문은 고객이 전자상거래시스템에 접속하여 자신이 원하는 상품을 검색하기 위해 상품명을 제시했을 때, 해당 고객을 포함한 기존의 고객들의 프로파일 중 고객의 구매 행위에 결정적으로 영향을 미칠 수 있는 요소를 선행사건, 구매 성향과 관계된 요소를 후행사건으로 규정하여 고객에 대한 상품 적합도를 계산하고 적합도가 높은 상품 위주로 자동적으로 검색하여 고객에게 제시할 수 있는 퍼지-조건부 확률을 이용한 전자상거래 검색 에이전트를 제시한다.

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원주 후류의 응집구조에 대한 자유흐름 난류강도의 영향 (The Effect of Free Stream Turbulence on the Coherent Structures in the near Wake of a Circular Cylinder)

  • 정양범;양종필
    • Journal of Advanced Marine Engineering and Technology
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    • 제18권1호
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    • pp.60-72
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    • 1994
  • The effect of free stream tubulence on the coherent structure in the near wake of a circular cylinder was investigated by a conditional sampling technique. The measurements were made from C.T.A. with hot wire I-probe and a Split-film sensor. Contours of phase-averaged velocity and vorticities were presented and discussed. It was found that the value of the vortex strength increased with increasing free stream turbulence which can enhance the roll-up of the shear layer.

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음향섭동에 의한 후류유동의 제어 (Wake Flow Control by Acoustic Perturbation)

  • 이종춘
    • Journal of Advanced Marine Engineering and Technology
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    • 제22권4호
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    • pp.451-459
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    • 1998
  • THe influence of internal acoustic exitation through a square prism on the turbulent wake flow characteristics was investigated. The intermediate wake region where is about ten times the respective length of the body was experimentally investigated using a conditional phase average technique. At first the static base pressures of square prism and the shedding frequencies have been measured at various internal acoustic exciation frequencies. The experiment were performed under the four cases of internal acoustic excitation frequencies 0Hz 30Hz($St_e$=0.09) 65Hz($St_e$=0.20) 120Hz($St_e$=0.38) And velocity vector fields were presented and discussed. The influence of acoustic exvitation frequencies on the structure of intermediate turbulent wake region is evident. As the internal acoustic frequency increased shedding frequency gradually increased and aerodynamic force decreased. Also it was found that the vortex shedding occurs dratically well and shedding frequency reached nearly the same value as the internal acoustic frequency. but above Strouhal number 0.3 the influence disappeared.

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Integer-Valued HAR(p) model with Poisson distribution for forecasting IPO volumes

  • SeongMin Yu;Eunju Hwang
    • Communications for Statistical Applications and Methods
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    • 제30권3호
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    • pp.273-289
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    • 2023
  • In this paper, we develop a new time series model for predicting IPO (initial public offering) data with non-negative integer value. The proposed model is based on integer-valued autoregressive (INAR) model with a Poisson thinning operator. Just as the heterogeneous autoregressive (HAR) model with daily, weekly and monthly averages in a form of cascade, the integer-valued heterogeneous autoregressive (INHAR) model is considered to reflect efficiently the long memory. The parameters of the INHAR model are estimated using the conditional least squares estimate and Yule-Walker estimate. Through simulations, bias and standard error are calculated to compare the performance of the estimates. Effects of model fitting to the Korea's IPO are evaluated using performance measures such as mean square error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE) etc. The results show that INHAR model provides better performance than traditional INAR model. The empirical analysis of the Korea's IPO indicates that our proposed model is efficient in forecasting monthly IPO volumes.

Improved Exact Inference in Logistic Regression Model

  • Kim, Donguk;Kim, Sooyeon
    • Communications for Statistical Applications and Methods
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    • 제10권2호
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    • pp.277-289
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    • 2003
  • We propose modified exact inferential methods in logistic regression model. Exact conditional distribution in logistic regression model is often highly discrete, and ordinary exact inference in logistic regression is conservative, because of the discreteness of the distribution. For the exact inference in logistic regression model we utilize the modified P-value. The modified P-value can not exceed the ordinary P-value, so the test of size $\alpha$ based on the modified P-value is less conservative. The modified exact confidence interval maintains at least a fixed confidence level but tends to be much narrower. The approach inverts results of a test with a modified P-value utilizing the test statistic and table probabilities in logistic regression model.

Improved Mid P-value Method for Statistical Inference in Three-Way Contingency Tables

  • Donguk Kim
    • Communications for Statistical Applications and Methods
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    • 제5권3호
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    • pp.905-926
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    • 1998
  • We propose a modified mid P-value method to reduce the conservativeness for the inference of conditional associations in three-way contingency tables. This improves the ordinary mfd P-value method. For $2{\times} 2${\times} K$ tables, we propose confidence intervals for an assumed common odds ratio based on inverting two separate one-sided tests using the modified mid P-value. Also, an alternative and usually even better ways of constructing intervals, based on Inverting a two-sided test, are presented. The actual probability of coverage of a 100($1-\alpha$)% confidence interval is centered about the nominal level, but the modified mid P-value approach gives actual coverage probability even closer to the nominal level than the ordinary mid P-value approach.

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의복소비가치에 따른 집단별 외모관리행동의 차이 (Differences of Appearance Management Behaviors among Clothing Consumption Value)

  • 김인숙
    • 한국의류산업학회지
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    • 제18권5호
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    • pp.606-616
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    • 2016
  • We intend an empirical assessment of examining the differences in the appearance management behaviors and demographic variables among groups classified by the clothing consumption values. The questionnaires are administered to 493 female and male adults above 20 years old in Seoul, Gyeonggi-do, Daegu and Kyungpook regions. For analysis of data from 478 respondents, descriptive statistics, cluster analysis, Cronbach's ${\alpha}$, ANOVA, Duncan test and ${\chi}^2$ test were applied. We show the following results. First, Factor analyses were employed for the clothing consumption values and appearance management behaviors. Six factors were for clothing consumption values: Individuality, appearance attractive, social, functional, conditional and fashion clothing consumption value. Four factors were for appearance management behaviors: weight training, skin care, hair care, make-up and clothing selection. According to clothing consumption values, four groups were classified: the passive, functional, social, and active group. We did cluster analysis to the appearance management behaviors of weight training, skin care, hair care, make-up and clothing selection. Second, the social and active groups were more interested in individuality, appearance attractive, social, functional, conditional and fashion clothing value. And they were also more involved in appearance management behaviors. Third, among the demographic variables, the single and female in 20s and 30s with higher level of education belonged to the active group. In this contribution, we find significant differences in the appearance management behavior and demographic variables classified by the clothing consumption values.

다변량 조건부 꼬리 기대값 (Multivariate conditional tail expectations)

  • 홍종선;김태우
    • 응용통계연구
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    • 제29권7호
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    • pp.1201-1212
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    • 2016
  • 시장위험 관리를 위한 Value at Risk(VaR)는 금융기관들이 선호하는 기법이지만, 투자가 실패한 경우에 손실금액에 대하여는 설명할 수 없다는 문제점이 있다. VaR의 한계를 보완하는 대안적인 위험측정도구인 Conditional Tail Expectation(CTE)는 VaR를 초과하는 조건부 기대값으로 정의된다. 포트폴리오에 대한 CTE를 추정하는 실제금융시장에서는. 일반적으로는 다변량 손실률을 일변량 분포로 변환하여 VaR을 추정하고 CTE를 구하지만, 본 연구에서는 다차원 분위벡터를 이용하여 다변량 CTE들을 제안한다. 그리고 일변량 CTE들의 관계를 확장하여 다변량 CTE들의 관계식을 유도하였다. 다양한 분산-공분산행렬을 갖는 이변량과 삼변량의 정규분포로부터 다변량 CTE들을 구하고 CTE들의 관계식을 구현하면서 고차원 분포로의 확장 가능성을 설명하였다. 이변량과 삼변량의 실증 예제를 통해 제안한 이론을 탐색하고, 기존의 CTE와 비교하였다. 다변량 변수들의 분산-공분산행렬과 다변량 분위벡터를 사용한 다변량 CTE가 일변량으로 변환하여 구한 CTE보다 작은 값을 갖는 것을 발견하였다. 그러므로 본 연구에서 제안한 다변량 CTE는 보다 적은 위험성을 나타내는 추정량이며, 포트폴리오를 구성하는 여러 기업을 동시에 고려하는 분산 투자 전략을 세우는 경우에 이런 다변량 CTE를 사용하는 적극적인 투자가 가능하다는 장점이 있다.