• Language and Information
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• v.14 no.1
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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.

• Journal of Korea Multimedia Society
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• v.17 no.11
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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'

• The Journal of Information Systems
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• v.28 no.3
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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.

• Journal of Digital Convergence
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• v.18 no.1
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• pp.301-307
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• 2020

In recent years, a recommendation system is introduced in many different fields with the beginning of the 5G era and making a considerably prominent appearance mainly in books, movies, and music. In such a recommendation system, however, the preference degrees of users are subjective and uncertain, which means that it is difficult to provide accurate recommendation service. There should be huge amounts of learning data and more accurate estimation technologies in order to improve the performance of a recommendation system. Trying to solve this problem, this study proposed a movie recommendation system based on Fuzzy-AHP and Word2vec. The proposed system used Fuzzy-AHP to make objective predictions about user preference and Word2vec to classify scraped data. The performance of the system was assessed by measuring the accuracy of Word2vec outcomes based on grid search and comparing movie ratings predicted by the system with those by the audience. The results show that the optimal accuracy of cross validation was 91.4%, which means excellent performance. The differences in move ratings between the system and the audience were compared with the Fuzzy-AHP system, and it was superior at approximately 10%.

• Korean Journal of Cognitive Science
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• v.24 no.1
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• pp.25-47
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• 2013

We conducted a psycholinguistic experiment in which participants orally produced sentences using a subject, a dative object, an accusative object, and a verb, provided just before the production. Results of the experiment are twofold: (i) Korean speakers basically produce the dative object earlier than the accusative one if the lengths of the objects are identical. (ii) If there is a length difference between the two objects, though, the longer one strongly tends to be placed before the shorter one, overriding the preference for 'dative-accusative' order. This 'long before short' preference which is generally observed in head-final languages appears to reflect the underlying tendency of the processing mechanism to put the heads of arguments and the predicate as closely as possible, thereby minimizing the cost for the processing of verb-argument structure.

• Korean Journal of Cognitive Science
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• v.17 no.4
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• pp.337-356
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• 2006

This research was conducted to see the impact of brightness, polarity, and hue diference on legibility and emotional effcts of the word. In the experiment 1, stimuli with three levels of brightness difference and two-typed polarity were used. The results showed that legibility, aesthetics, and preference increased with increasing brightness difference. In the experiment 2, the same stimuli if experiment 1 included four hues: red, green, blue, yellow. As a result, the effects of brightness and polarity and the interaction effect of brightness and polarity on legibility were significant. Also, the effects of brightness, polarity, and hue and the interaction effect of brightness and hue on aesthetics and preference were significant. These results showed that legibility, aesthetics, and preference increased with increasing brightness difference of word and background and positive polarity was better than negative. Aesthetics and preference rating increased according to the following order: red, blue, green, yellow. In addition, the interaction effect of brightness and polarity on legibility was because reaction time of negative polarity was longer than positive at the small brightness difference condition. The interaction effect of brightness and hue on aesthetics and preference ws because the aesthetics rating of hue at the large brightness difference condition had significant difference compared with small brightness difference. In the experiment 3, participants rated text designs and simple color stimuli with 18 emotional adjectives to see the similarity of their emotion. The conclusion was that to reflect the subjective feelings of a rotor on the text design, it would be appropriate to use the rotor on background of the text design.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11b
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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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.5 s.110
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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.

• Journal of Biomedical Engineering Research
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• v.30 no.2
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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.

• Journal of the East Asian Society of Dietary Life
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• v.10 no.1
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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.