• 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.

• 한국멀티미디어학회논문지
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• 제17권11호
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• pp.1286-1295
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• 2014

This paper suggests the way that it could improve the reliability about preference of user's feedback by adding weighting factor on sentiment analysis, and efficiently make a sentiment analysis of users' emotional perspective on the big data massively generated on twitter. To solve errors on earlier studies, this paper has improved recall and precision of sensibility determination by using sensibility dictionary subdivided sentiment polarity based on the level of sensibility and given impotance to sensibility determination by populating slang, new words, emoticons and idiomatic expressions not in the system dictionary. It has considered the context through conjunctive adverbs fixed in korean characteristics which are free to the word order. It also recognize sensibility words such as TF(Term Frequency), RT(Retweet), Follower which are weighting factors of preference and has increased reliability of preference analysis considering weight on 'a very emotional tweet', 'a recognised tweet from users' and 'a tweeter influencer'

• 한국정보시스템학회지:정보시스템연구
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• 제28권3호
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• pp.25-38
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• 2019

Purpose This study aims to empirically analyze which factors affect image and preference of YouTube beauty channels. Some practical and academic implications are presented through empirical research. Design/methodology/approach For this purpose, the six affecting factors were suggested on the basis of previous studies. We proposed image quality, user attitude, empirical value, economics, and awareness as independent variables and channel image and channel preference as dependent variables in order to investigate the causal relationships among the research variables. We surveyed 311 users who had experience in using YouTube Beauty channel and analyzed the data by using a statistical package. Findings This study showed that the channel image has a partial mediating effect between the affecting variables and the channel preference. The results provided some insights and information to increase the number of subscribers and site views. Several suggestions were carefully made.

• 디지털융복합연구
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• 제18권1호
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• pp.301-307
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• 2020

최근 추천 시스템은 5G 시대의 시작과 동시에 여러 분야에서 도입하고 있으며, 주로 도서나 영화, 음악 분야의 서비스에서 크게 두각을 나타내고 있다. 그러나 이러한 추천 시스템에서 사용자마다 선호하는 정도가 주관적이고, 불확실하여 정확한 추천 서비스를 제공하기가 어렵다. 추천 시스템의 성능을 향상시키기 위해서는 많은 양의 학습 데이터가 필요하며, 추론 기술이 보다 정확해야 한다. 이러한 문제점을 해결하기 위하여 본 연구에서는 Fuzzy-AHP와 Word2Vec 학습 기법을 이용한 영화 추천 시스템을 제안하였다. 본 시스템에서는 사용자의 선호도를 객관적으로 예측하기 위해 Fuzzy-AHP를 사용하였으며, 스크레이핑한 데이터를 분류하기 위해 Word2Vec 학습 기법을 사용하였다. 본 시스템의 성능을 평가하기 위해 그리드 서치를 이용하여 Word2Vec 학습 결과의 정확도를 측정하였고, 그 후 본 시스템이 예측한 평점과 관객들이 평가한 영화의 평점 간 차이를 비교하였다. 그 결과 최적의 교차 검증 정확도가 91.4%로 우수한 성능을 나타내었으며, 예측한 평점과 관객들이 평가한 영화의 평점 간 차이를 Fuzzy-AHP 시스템과 비교한 결과 10% 정도 우수함을 확인할 수 있었다.

• 인지과학
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• 제24권1호
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• pp.25-47
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• 2013

한국어 원어민을 대상으로 제시된 주어, 간접(여격) 목적어, 직접(대격) 목적어, 그리고 동사를 자유로이 배열하여 문장을 발화하도록 하는 실시간 문장산출 실험을 실시하였다. 실험의 결과는 (i) 간접 목적어와 직접 목적어의 길이가 동일할 경우 간접 목적어를 직접 목적어 앞에 두는 어순이 선호되지만, (ii) 관계절의 수식을 통해 두 목적어의 길이를 달리 했을 경우 격과 무관하게 길이가 긴 목적어를 짧은 목적어 앞에 두는 어순이 선호된다는 것을 입증하고 있다. 핵어후치 언어에서 관찰되는 이러한 'long before short' 선호도는 논항의 핵어들과 술어를 되도록 문장 끝부분에 밀집시켜 논항구조 처리의 효율성을 높이고자 하는 언어처리기제의 특성에 따른 것이라고 설명할 수 있다.

• 인지과학
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• 제17권4호
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• pp.337-356
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• 2006

본 연구에서는 시각디스플레이에서 단어와 배경간의 밝기, 대비부호, 색상 차이가 가독성 및 감성에 미치는 효과를 살펴보았다. 실험 1에서는 밝기차이(대, 중, 소)${\times}$대비부호(정적, 부적) 조건에 따른 가독성, 심미성, 선호도의 효과를 알아보았다. 실험 1의 결과, 밝기 차이가 커짐에 따라 가독성, 심미성, 선호도가 증가하였다. 실험 2에서는 실험 1 조건에 네 가지 색상 요인(초록, 빨강, 노랑, 파랑)을 추가하여 수행하였다. 그 결과 가독성에서는 밝기와 대비부호의 주효과, 밝기와 대비부호간의 상호작용효과가 유의미하였으며, 심미성과 선호도에서는 밝기, 대비부호, 색상의 주효과, 밝기와 색상간의 상호작용효과가 유의미하였다. 즉 밝기의 차이가 커짐에 따라 가독성, 심미성, 선호도가 증가하였으며, 정적대비가 부적대비에 비해 가독성, 심미성, 선호도가 더 좋았으며, 색상은 빨강, 파랑, 초록, 노랑 순으로 심미성과 선호도가 높은 결과를 보였다. 또한 가독성에서 밝기와 대비부호간의 상호작용효과는 밝기의 차이가 작은 조건에서 부적대비가 정적대비보다 반응시간이 길게 나타났기 때문인 것으로 보인다. 심미성과 선호도에서 밝기와 색상간의 상호작용효과가 나타난 것은 밝기 차이가 작은 조건에 비해 큰 조건에서 색상에 따른 심미성효과가 유의미하게 차이가 있었기 때문인 것으로 보인다. 실험 3에서는 텍스트 디자인과 단일색을 대상으로 18개의 감성 어휘를 평정하게 하여 감성의 유사성을 측정하였다. 그 결과, 특정 색이 지닌 주관적인 느낌이 텍스트 디자인에 잘 반영되기 위해서는 배경에 그 색을 사용하는 것이 더 적절하다는 결론을 얻었다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 추계 학술대회논문집(수송기계편)
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• pp.174-179
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• 2005

In automotive engineering, the brand sound is one of the important advantage strategy in a car company. For the design of brand sound, the selection of descriptive word for a car sound is one of major works in automotive sound quality research. In paper, booming sound and rumbling sound, which are professional words used by NVH engineers are used for the design of brand sound. We employed sound metrics which are the subjective parameter used in psychoacoustics. According to most research results, the relationship between subjective evaluations and sound metrics has nonlinear characteristics and is very complex. In order to link these subjective evaluations to sound metrics, the artificial neural network technology has been applied to two-dimensional sound quality index for a passenger car. These indexes is used for 46 passenger cars, which are samples of famous cars in the world. Also the preference in car sounds is evaluated by the trained NVH engineers. We coupled this preference with booming and rumbling sounds by using artificial neural network. In future, the two -dimensional sound index and preference index are very useful fur the development of brand sound in passenger cars.

• 한국소음진동공학회논문집
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• 제16권5호
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• pp.457-469
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• 2006

In automotive engineering, the brand sound is one of the important advantage strategies in a car company. For the design of brand sound, the selection of descriptive word for a car sound is one of major works in automotive sound quality research. In this paper, booming and rumbling sound, which are professional words used by sound and vibration engineers are used for the design of brand sound. We employed sound quality metrics, which are used in the psychoacoustics. By most research results, the relationship between subjective evaluations and sound quality metrics has nonlinear characteristics. In order to correlate these subjective evaluations with sound quality metrics, the artificial neural network technology has been applied to two-dimensional sound quality index for a passenger car. These indexes are used for 46 passenger cars, which are samples of the famous cars around the world. Also a preference evaluation for car sound was carried out by sound and vibration engineers. We coupled this preference with booming and rumbling sounds by using artificial neural network. In future, the two dimensional sound and preference index will be very useful to develop brand sound in passenger cars.

• 대한의용생체공학회:의공학회지
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• 제30권2호
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• pp.169-178
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• 2009

In this study, we suggest Korean nonlinear fitting formula (KNFF) to maximize speech intelligibility for digital hearing aids based on NAL-NL1 (NAL-nonlinear, version 1). KNFF was derived from the same procedure which is used for deriving NAL-NL1. KNFF consider the long-term average speech spectrum of Korean instead of English because the frequency characteristic of Korean is different from that of English. New insertion gains of KNFF were derived using the SII (speech intelligibility index) program provided by ANSI. In addition, the insertion gains were modified to maximize the intelligibility of high frequency words. To verify effect of the new fitting gain, we performed speech discrimination test (SDT) and preference test using the hearing loss simulator from NOISH. In the SDT, a word set as test material consists of 50 1-syllable word generally used in hearing clinic. As a result of the test, in case of moderate hearing loss with severe loss on high frequency, the SDT scores of KNFF was more improved about 3.2% than NAL-NLl and about 6% in case of the sever hearing loss. Finally we have obtained the result that it was the effective way to increase gain of mid-high frequency bands and to decrease gain of low frequency bands in order to maximize speech intelligibility of Korean.

• 동아시아식생활학회지
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• 제10권1호
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• pp.71-76
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• 2000

This study was carried out in order to investigated the degree of expansion, textural and sensory characteristics of Yukwa made from various cultivars of waxy rice, With 5 varieties of waxy rice and a nonwaxy rice, Yukwa were prepared by the standardized method that had been established optimum preparation conditions. Yukwa made from Shinsunchalbyeo and Whasunchal showed lower degree of expansion than Hangangchalbyeo and IR 29, but showed higher crispness and softer texture among tested waxy rice cultivars. Sensory characteristics of these cultivars showed high score in flavor, crispness and preference. Whasunchalbyeo and Shinsunchalbyeo were appropriate varieties for Yukwa preparation and they were both short grain in length/width. Whasunchalbyeo has the highest score of water uptake and reducing sugar content in Key word.