• 한국언어정보학회지:언어와정보
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• 제14권1호
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• pp.113-144
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• 2010

The primary goal of this paper is to find a feasible way to answer the question: Does the similarity in meaning between verbs relate to the similarity in their subcategorization? In order to answer this question in a rather concrete way on the basis of a large set of English verbs, this study made use of various language resources, tools, and statistical methodologies. We first compiled a list of 678 verbs that were selected from the most and second most frequent word lists from the Colins Cobuild English Dictionary, which also appeared in WordNet 3.0. We calculated similarity measures between all the pairs of the words based on the 'jcn' algorithm (Jiang and Conrath, 1997) implemented in the WordNet::Similarity module (Pedersen, Patwardhan, and Michelizzi, 2004). The clustering process followed, first building similarity matrices out of the similarity measure values, next drawing dendrograms on the basis of the matricies, then finally getting 177 meaningful clusters (covering 437 verbs) that passed a certain level set by z-score. The subcategorization frames and their frequency values were taken from the ICE-GB. In order to calculate the Selectional Preference Strength (SPS) of the relationship between a verb and its subcategorizations, we relied on the Kullback-Leibler Divergence model (Resnik, 1996). The SPS values of the verbs in the same cluster were compared with each other, which served to give the statistical values that indicate how much the SPS values overlap between the subcategorization frames of the verbs. Our final analysis shows that the degree of overlap, or the relationship between semantic similarity and the subcategorization frames of the verbs in English, is equally spread out from the 'very strongly related' to the 'very weakly related'. Some semantically similar verbs share a lot in terms of their subcategorization frames, and some others indicate an average degree of strength in the relationship, while the others, though still semantically similar, tend to share little in their subcategorization frames.

• 대한디지털의료영상학회논문지
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• 제11권2호
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• pp.93-99
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• 2009

This conclusion was from the 3rd grade students of radiologic technology of Daegu Health College who already taken the hospital practice. 231 students answer our question and this study used sampling method. The contents of Questionnaire consisted of normal facts of respondent, Training satisfaction, Training Methods, Practice Environment of Hospital, Problem in Practice Hospital, Before and after views, etc. The statistical program SPSS/Win 10.0 version was used to see the results of the survey data used in. The response contents of brief question were separetely checked and clean.

• 아동학회지
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• 제12권2호
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• pp.18-36
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• 1991

The developmental self-knowledge from preschool to early adolescence was studied from a cognitive-structural perspective. Responses of the subjects to the question "Who am I?" were analyzed by means of a 29-category scoring system. The question was administered to 250 boys and 229 girls from kindergartens, elementary schools and middle schools in Seoul. One way-ANOVA and Duncan test were utilized for the statistical analysis. The major findings of the present study showed that with increasing age there was (1) a significant increase and diversification of self-knowledge. (2) an individual's self-knowledge became more abstract and less concrete, and (3) self-descriptions shifted from the physical to the psychological self.

• 한국조사연구학회지:조사연구
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• 제1권1호
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• pp.21-43
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• 2000

전화면접을 개별직접면접에 대한 매력적 대안이 될 수 있지만 두 가지 자료 수집방식에서 동일한 결과를 얻을 수 있는지에 대하여는 많은 의문이 제기되어 왔다. 이러한 의문에 대답하기 위해서는 i)전화면접에 대한 피면접자의 선호도, 면접의 속도, 개방질문에 대한 응답의 상세성, 미응답 항목의 비율 등 직접효과 ii) 통계적 추정량 iii) 면접자의 차이와 자료수집양식 등의 관점에서 경험적 문헌검토를 하였다. 이러한 차이는 전화면접에 대한 사회적 소망성 효과, 서베이 질문에 대한 인지능력 및 양식효과와 면접자 효과로 설명될 수 있다.

• 한국항공운항학회지
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• 제6권1호
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• pp.21-29
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• 1998

The purpose of the present paper is to determine the time required and error tolerance limits for flight data computation. The results of statistical analysis showed that the calculator side computation required about 50 seconds for each question and wind side computation needed about 115 seconds for each question. In case of error tolerance limits, it was found that the error tolerance limit for altitude computation war 90 feet and two knots of interval was recommanded for the speed computation in calculator side, and one degree of interval for heading computation and five knots interval for speed computation in wind side.

• 융합경영연구
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• 제7권3호
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• pp.29-43
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• 2019

Research Purpose - The purpose of this study was to investigate marketing stimulation and impulsive buying of Internet shopping mall. Research Question - Despite these unstable factors, the Internet shopping mall market has become more popular than traditional distribution channels such as department stores and discount stores due to the increase in the number of Internet users, a gradual increase in the consumption of high-priced items. Research Method - The data were collected from 301 women living in Seoul, Gyeonggi, Gwangju, Daegu, and Gyeongnam province in Korea on May 2018. Statistical methods used in the study were frequency, F-test, Duncan test, factor analysis, Cronbach's α, correlation coefficient, and multiple regression. Result - All The reliability of these questions is Cronbach's α =. 775. Factor 5, which is 12.367 % explanatory power, is said to consist of three questions: price, discount bag, and no-carrying; thus, the reliability of the question is Cronbachs' α. The ratio of the five factors in body random cases was 66.096 %, and the reliability of the questions was higher than. 770 as a result of the reliability analysis.

• 사상체질의학회지
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• 제15권2호
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• pp.64-74
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• 2003

Objectives : To evaluate the properness and effectiveness of the question categories concerning 'total physiognomy', used in Iksan Wonkwang Oriental Medicine. Methods: We statistically analyzed data from those 1335 patients focussing on 'relative discrimination ability' to sasang constructions and 'response ratio'. Patients included in this research are only those who had been well treated in Iksan Wonkwang Oriental Medicine during the Period of three years from 2000 to 2002. The data are obtained through the electronic chart developed by Kim Jong-Yeol, and analyzed using the statistical Package SPSS. Results: The first category for discriminating Taeum type, 'heavy and looking steady', has more discriminating power and effectiveness among women than men, and especially in wemen with an age of 21 or more. The second category for discriminating Soeum type, 'delicate and modest', is more discriminating and effective among men than women, and mostly among men with ages 21-40. The third category for Soyang type, 'fast and brave', is almost equally discriminating and effective to both women and men, especially among women with ages 40 or less and among men with ages 21 or more. Finally, the forth category for discriminating Taeyang type, 'progressive', is neither discriminating nor effective among most the women than men in all age groups. Conclusions: The definition of 'relative discriminating power of constitution' and 'response ratio' are well evaluating the properness and effectiveness of the question categories regarding 'total physiognomy'. The first category is most discriminating and effective among women with ages 20 or less, and the second among 21-40 year old men, the third among women with ages 40 or less and among men with ages 21 or over. The forth category is neither discriminating nor effective.

• 한국조사연구학회지:조사연구
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• 제13권1호
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• pp.113-134
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• 2012

대통령 지지도는 대통령 자신에 대한 정치적인 성취뿐만 아니라 국민과 관련된 정책 결정 및 추진에 있어 중요한 기준이 된다는 측면에서 매우 중요하다. 그럼에도 불구하고 기존의 대통령 지지도 측정 방식은 현실적인 체감적인 만족과는 상당한 격차를 느끼게 할 정도로 측정 자체에 많은 문제점을 보여 주었다. 본 연구의 목적은 대통령의 국정수행 지지도를 측정하는 문항의 구성과 조사결과의 활용에 있어 현행 방식의 문제점을 지적하고 새로운 개선방안을 제시하기 위함이다. 첫째로 설문기획 측면에서 '대통령 국정수행'을 평가하는 성격의 설문구성은 부적절하다는 것을 도출할 수 있었다. '대통령으로서의 일'을 모르는 응답자들이 '잘하는지와 못하는지'를 알지 못하기 때문이다. 그리고 보기 척도에서도 응답자의 응답가능성을 기초할 때 4점 척도의 보기 구성보다 5점 척도의 보기 구성이 타당함을 밝힐 수 있었다. 둘째로 통계분석 측면에서 대통령 국정수행 평가 문항(잘하는지와 못하는지를 응답하는 문항)과 정책관련 문항, 직접적으로 대통령에 대한 지지도를 물어보는 문항과의 상관분석을 시도하였다. 이를 통해 결국 대통령 국정수행 평가는 적절하지 않으며 대통령에 대해 직접적인 지지 여부를 물어보는 것이 가장 설명력이 있다는 것을 알 수 있었다. 마지막으로 결과활용 측면에서 대통령의 지지도가 '높고 낮음'은 언론 매체의 주관적인 판단에 의존할 것이 아니라 조사 자체의 응답자들을 대상으로 상대적으로 도출하여 대통령 지지도의 결과값과 비교하는 것이 더 설득력이 있다고 보았다.

• 한국조사연구학회:학술대회논문집
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• 한국조사연구학회 2011년도 추계학술대회 발표논문집
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• pp.63-81
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• 2011

본 연구의 목적은 대통령의 국정 수행 지지도를 측정하는 문항의 구성과 조사 결과의 활용에 있어 현행 방식의 문제점을 지적하고 새로운 개선방안을 제시하기 위함이다. 대통령 지지도는 대통령 자신에 대한 정치적인 성취뿐만 아니라 국민과 관련된 정책 결정 및 추진에 있어 중요한 기준이 된다는 측면에서 매우 중요하다. 그럼에도 불구하고 기존의 대통령 지지도 측정 방식은 현실적인 체감 만족과는 상당한 격차를 느끼게 할 정도로 많은 문제점을 보여 주었다. 이 연구를 통해 첫째로 설문기획 측면에서 '대통령 국정 수행'을 평가하는 성격의 설문 구성은 부적절하다는 것을 도출할 수 있었다. '대통령으로서의 일'을 모르는 응답자들이 '잘하는지와 못하는지'를 알지 못하기 때문이다. 그리고 보기 척도에서도 응답자의 응답가능성을 기초할 때 4점척도 보기 구성보다 5점척도 보기 구성이 타당함을 밝힐 수 있었다. 둘째로 통계분석 측면에서 대통령 국정수행 평가 문항(잘하는 지와 못하는 지를 응답하는 문항)과 정책관련 문항, 직접적으로 대통령에 대한 지지도를 물어보는 문항과의 상관분석을 시도하였다. 이를 통해 결국 대통령 국정 수행 평가는 적절하지 않으며 대통령에 대해 직접적인 지지 여부를 물어보는 것이 가장 설명력이 있다는 것을 알 수 있었다. 마지막으로 결과활용 측면에서 대통령의 지지도가 '높고 낮음'은 언론 매체의 주관적인 판단에 의존할 것이 아니라 조사 자체의 응답자들을 대상으로 상대적으로 도출하여 대통령 지지도의 결과값과 비교하는 것이 더 설득력이 있다고 보았다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권10호
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• pp.3230-3255
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• 2022

Causality mining in NLP is a significant area of interest, which benefits in many daily life applications, including decision making, business risk management, question answering, future event prediction, scenario generation, and information retrieval. Mining those causalities was a challenging and open problem for the prior non-statistical and statistical techniques using web sources that required hand-crafted linguistics patterns for feature engineering, which were subject to domain knowledge and required much human effort. Those studies overlooked implicit, ambiguous, and heterogeneous causality and focused on explicit causality mining. In contrast to statistical and non-statistical approaches, we present Bidirectional Encoder Representations from Transformers (BERT) integrated with Multi-level Feature Networks (MFN) for causality recognition, called BERT+MFN for causality recognition in noisy and informal web datasets without human-designed features. In our model, MFN consists of a three-column knowledge-oriented network (TC-KN), bi-LSTM, and Relation Network (RN) that mine causality information at the segment level. BERT captures semantic features at the word level. We perform experiments on Alternative Lexicalization (AltLexes) datasets. The experimental outcomes show that our model outperforms baseline causality and text mining techniques.