• Korean Journal of Cognitive Science
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• v.11 no.3_4
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• pp.83-93
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• 2000

The effect of immediate and delayed recognition memory on event-related potential (ERP) was studied using a continuous recognition memory task and event-related potential (ERP). Among 240 stimulus words 40 words were not repeated. 100 were immediately repeated and 100 were repeated after 5 intervening words. All words presented only once during the experiment were referred to as new words. Subjects responded faster and more accurately to words repeated immediately than to new words a and to those repeated after intervening words. In terms of ERP results the immediately repeated words were associated with large P300 amplitude, early P300 latency and a absence of N400. while words repeated after a delay were associated with small P300 a amplitude. late P300 latency and the presence of N400. N400 was elicited only to new w words and to those repeated after a delay. The general morphology of the waveform was s similar for three stimulus-presentation conditions until around 3l0ms after the onset of stimulus. These results indicate that immediate and delayed recognition memory could be dissociated into two distinct processes possibly being mediated by different cerebral mechanism, and the dissociation between two types of recognition memory emerges around 3l0ms poststim'ulus. The immediate and delayed recognition memory for words are considered in terms of template matching and memory searching.

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.105-120
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• 2012

This study aimed to develop a Korean emotion vocabulary list that functions as an important tool in understanding human feelings. In doing so, the focus was on the careful extraction of most widely used feeling words, as well as categorization into groups of emotion(s) in relation to its meaning when used in real life. A total of 12 professionals (including Korean major graduate students) partook in the study. Using the Korean 'word frequency list' developed by Yonsei University and through various sorting processes, the study condensed the original 64,666 emotion words into a finalized 504 words. In the next step, a total of 80 social work students evaluated and classified each word for its meaning and into any of the following categories that seem most appropriate for inclusion: 'happiness', 'sadness', 'fear', 'anger', 'disgust', 'surprise', 'interest', 'boredom', 'pain', 'neutral', and 'other'. Findings showed that, of the 504 feeling words, 426 words expressed a single emotion, whereas 72 words reflected two emotions (i.e., same word indicating two distinct emotions), and 6 words showing three emotions. Of the 426 words that represent a single emotion, 'sadness' was predominant, followed by 'anger' and 'happiness'. Amongst 72 words that showed two emotions were mostly a combination of 'anger' and 'disgust', followed by 'sadness' and 'fear', and 'happiness' and 'interest'. The significance of the study is on the development of a most adaptive list of Korean feeling words that can be meticulously combined with other emotion signals such as facial expression in optimizing emotion recognition research, particularly in the Human-Computer Interface (HCI) area. The identification of feeling words that connote more than one emotion is also noteworthy.

• The Journal of Korean Medical History
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• v.28 no.2
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• pp.37-45
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• 2015

Objectives : A quantitative analysis on the vocabulary in the English translation version of Donguibogam. Methods : This study quantitatively analyzed the English-translated texts of Donguibogam with the Corpus-based analysis, and compared the quantitative results analyzing the texts of original Donguibogam. Results : As the results from conducting the corpus analysis on the English-translation version of Donguibogam, it was found that the number of total words (Token) was about 1,207,376, and the all types of used words were about 20.495 and the TTR (Type/Token Rate) was 1.69. The accumulation rate reaching to the high-ranking 1000 words was 83.54%, and the accumulation rate reaching to the high-ranking 2000 words was 90.82%. As the words having the high-ranking frequency, the function words like 'the, and of, is' mainly appeared, and for the content words, the words like 'randix, qi, rhizoma and water' were appeared in multi frequencies. As the results from comparing them with the corpus analysis results of original version of Donguibogam, it was found that the TTR was higher in the English translation version than that of original version. The compositions of function words and contents words having high-ranking frequencies were similar between the English translation version and the original version of Donguibogam. The both versions were also similar in that their statements in the parts of 'Remedies' and 'Acupuncture' showed higher composition rate of contents words than the rate of function words. Conclusions : The vocabulary in the English translation version of Donguibogam showed that this book was a book keeping the complete form of sentence and an Korean medical book at the same time. Meanwhile, the English translation version of Donguibogam had some problems like the unification of vocabulary due to several translators, and the incomplete delivery of word's meanings from the Chinese character-culture area to the English-culture area, and these problems are considered as the matters to be considered in a work translating Korean old medical books in English.

• MALSORI
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• no.40
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• pp.51-63
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• 2000

There are sentences where sentence stress is imposed on a specific word. These sentences are called 'focused sentences'. The purpose of this paper is to investigate the variation of pitch, duration, amplitude in focused words. It is noted that pitch of a focused word is higher than that of unfocused words irrespective of the accentual pattern, and that contour tones such as HL or LH are realized longer when these tones appear in focused words. Not only the noun but also the following particle like '-boda' is higher when these words are in focus. Hence pitch is proved to be the most salient prosodic feature of the focused sentence.

• Journal of Engineering Education Research
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• v.17 no.4
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• pp.54-57
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• 2014

This paper investigated the influence of foreign words, otherwise known as loan words, on global communication abilities of university students from two non English-speaking countries: Korea and Japan. To survey the understanding and usage of foreign words which are from English language and used frequently in daily conversation, questionnaires were administered to Korean and Japanese university students majoring in engineering who shared similar linguistic backgrounds. The results were analyzed from global communication viewpoint. Based on the results, methods for improving global communication skills in engineering education were proposed.

• Korean Journal of English Language and Linguistics
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• v.2 no.1
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• pp.53-76
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• 2002

This paper aims to review Hammond's (1999) analysis of English word stress and propose an alternative by exploring two questions: Why English words display flexible stress patterns and what are the conditions all English words have to obey. As answers to the questions I propose an invisible suffix after words with final stress, foot structures with two levels, and four constraints, two of them are attained by revision of Hammond's. As long as words satisfy the constraints, more than one foot structures are allowed. That is why the English lexicon displays flexibility.

• Speech Sciences
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• v.8 no.3
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• pp.75-91
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• 2001

Nowadays, computer-mediated communications such as chatting and e-mail are widely used in younger generation. It has been known that the communicating words used by on-line users (so-called netizens) are quite different from those used by ordinary people. That is, the words are generally characterized by shortened, mimetic and onomatopoeic words, and the netizens also use various types of emoticon expressed like signs or symbols. This can cause some orthographic as well as cultural problems. This paper investigates some statistical data in PC-based communications, analyzes the general characteristics, and provides some explanations.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.105-122
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• 2019

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods.

• Science of Emotion and Sensibility
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• v.14 no.2
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• pp.207-220
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• 2011

The purpose of this study is to investigate sensibility words related with eco-friendly in the two media fashion magazines and internet newspapers and to analysis their appearance frequency and changes by the year through 1999~2010. Most frequently used words are 'nature, eco, cotton, natural fiber, health, fresh, clear, preservation, harmony, com fiber, and Lohas'. The words are divided in 4 groups: 'Nature/Environment, Material/Fiber, Human, and Adjectives/Micell'. A point of appearing time is analyzed: 'ecology, memory-shape material, organic, spa' were used before 2000, 'nature environment, eco-friendly, stretch material, wellbeing, substitute, recycling' were in 2000-2001, 'smart material, eco material, green' in 2002-2003, 'coolbiz, Lohas, natural dye' in 2004-2005, 'herb medicine, sustainable, warmbiz' in 2006-2007, 'greensumer, greenlife, solar energy, forest bath' in 2008-2009. Looking into their changes, in early 2000, the words of eco-friendly emotion and sensibility had appeared frequently relatively, but later on they decreased, and again recently increased showing highest appearing frequency. 'Nature/Environment' words have appeared recently very much, while 'Human' sensibility words have not changed much or decreased a little. 'Adjective/Micell' words has increased little bit recently. 'Material/Fiber' words showed decrease at fashion magazine, while they increased at the pages of internet news.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.425-432
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• 2017

The purpose of this study is to analyze mission statements of social welfare centers. For this, we collected mission statements of 385 social welfare centers nationwide. We analyzed data using the NVivo 10 program. Analysis results found the total number of collected words was 1,401. The number of words corresponding to the target of organizations was 448 (32.0%), the number of words corresponding to problems was 51 (3.6%), the number of words corresponding to the directionality 118 (8.4%), the number of words corresponding to strategy was 545 (38.9%), and the number of words corresponding to organization's image was 239 (17.1%). Second, the words of the intervention target were resident of community, local community and community. Intervention issues included community problems, poverty, and social isolation. The words of the organizational directivity included welfare community/village, social welfare, and empowerment. Words related to organizational strategy were formation/building, sharing/serving, and improvement/development/improvement. Words related to the organizational image included in the mission statements were the welfare center, we, the professional agency, and the neighbors. By analyzing the mission statements, we found that social welfare centers portrayed its identity based on 'locality'. The distribution of the words related to the community was high in both the target, target, and direction. The limitations of this study include the exclusion of analyzing the relationship between organizational mission and organizational performance. This should be considered in future studies.