• KIISE Transactions on Computing Practices
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• v.20 no.12
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• pp.700-705
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• 2014

An anagram is a form of word play to find a new word from a set of given alphabet letters. Good human anagram solvers use the strategy of bigrams. They explore a constraint satisfaction network in parallel and answers consequently pop out quickly. In this paper, we propose a molecular computational algorithm using the same process as this. We encoded letters into DNA sequences and made bigrams and then words by connecting the letter sequences. From letters and bigrams, we performed DNA hybridization, ligation, gel electrophoresis and finally, extraction and separation to extract bigrams. From the matched bigrams and words, we performed the four molecular operations again to distinguish between right and wrong results. Experimental results show that our molecular computer can identify cor rect answers and incorrect answers. Our work shows a new possibility for modeling the cognitive and parallel thinking process of a human.

• KIISE Transactions on Computing Practices
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• v.22 no.6
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• pp.290-295
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• 2016

Recently, folksonomy-based image-sharing sites where users cooperatively make and utilize tags of image annotation have been gaining popularity. Typically, these sites retrieve images for a user request using simple text-based matching and display retrieved images in the form of photo stream. However, these tags are personal and subjective and images are not categorized, which results in poor retrieval accuracy and low user satisfaction. In this paper, we propose a categorization scheme for folksonomy images which can improve the retrieval accuracy in the tag-based image retrieval systems. Consequently, images are classified by the semantic similarity using text-information and image-information generated on the folksonomy. To evaluate the performance of our proposed scheme, we collect folksonomy images and categorize them using text features and image features. And then, we compare its retrieval accuracy with that of existing systems.

• Journal of the Korean Society for Library and Information Science
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• v.27
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• pp.215-228
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• 1994

This study is to analyze the background and circumstances of the bibliographical description method appearing in the Hong-ssi Tok-so-rok, or an annotated classified bibliography of Korean and Chinese books edited for the Hongs and their clan. The conclusions are as follows. Each entries of the bibliography are entered under titles, and generally followed by bibliographic elements of volumes, written age, author's name, functional word of authorship, and annotation. The written age is stated by the dynasty name for the first authors within each classes. However some anonymous works and government compiled works are recorded the king's shrine name or the reign title. Entries of the bibliography are arranged by the chronological order in each classes. The writer's name is generally described by 'surname + given name'. However it is sometimes also recorded in the one of the following forms; Appellation (hao, 호) or posthumous title + surname + given name. Sumame + appellation or posthumous title + given name. Appellation ( (hao, 호) or posthumous title + sumame + Sonsaeng (선행) + given name. Sumame + government position title + given name. Appellation (hao, 호) + surname + cha(자, master). surname + ssi(씨). ect. Married women's names are stated by her husband's surname followed by the Chinese character 부 or 절부 which signifies wife or virtuous women, and then her given name. The works written or compiled by King's order (명찬서) are generally described in the form of 명제신+ functional word of authorship. Names of government agencies are occasionally stated as the authors' for the government publications or government compiled works. The functional words of authorship are described in the phrase of 소작야, 소편야 instead of 저, 찬, ect. It is more noticeable that in the case of the collections of individual writers' works the wording of 지문야, 지시야 is written after the name of the author. More complicated descriptive forms are seen in the entries of works for the shared authorship and mixed responsibility. Two or more than two monographic works of the same author classed in the same class are annotated all together.

• The KIPS Transactions:PartD
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• v.10D no.1
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• pp.57-66
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• 2003

With the development of the internet and computer, the amount of information through the internet is increasing rapidly and it is managed in document form. For this reason, the research into the method to manage for a large amount of document in an effective way is necessary. The document clustering is integrated documents to subject by classifying a set of documents through their similarity among them. Accordingly, the document clustering can be used in exploring and searching a document and it can increased accuracy of search. This paper proposes an efficient incremental cluttering method for a set of documents increase gradually. The incremental document clustering algorithm assigns a set of new documents to the legacy clusters which have been identified in advance. In addition, to improve the correctness of the clustering, removing the stop words can be proposed and the weight of the word can be calculated by the proposed TF$\times$NIDF function.

• Journal of Korea Game Society
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• v.17 no.2
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• pp.135-144
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• 2017

Sentiment analysis refers to a way of analyzing the writer's subjective opinions or feelings through text. For effective sentiment analysis, it is essential to build emotional word polarity lexicon. This paper introduces a crowdsourcing-based game that we have developed for efficiently building a polarity lexicon in Korean. First, we collected a corpus from the relating Internet communities using a crawler, and we classified them into words using the Twitter POS analyzer. These POS-tagged words are provided as a form of mobile platform based tagging game in which the players voluntarily tagged the polarities of the words, and then the result was collected into the database. So far we have tagged the polarities of about 1200 words. We expect that our research can contribute to the Korean sentiment analysis research especially in the game domain by collecting more emotional word data in the future.

• Journal of the Korea Safety Management & Science
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• v.13 no.3
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• pp.29-35
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• 2011

Safety and health related information for the proper use and handling of pesticides is usually printed on the surface of the pesticide products (bottle type or bag type) in the form of texts. But, the guidelines or standards for the appropriate presentation of the texts for the pesticide products are most vague or not practical. Thus, this study aimed to provide the preliminary guidelines for the text sizes based on the legibility experiments. Total twenty subjects from two age groups (young: n=10, old: n=10, five males and five females in each group) participated in the experiment. First, subjects read the text cards presented in the distance of 50cm from the eyes of the subjects. Eight different text card sets were prepared for different font type(thick gothic-type and fine gothic-type), thickness of font(plain and bold), and number of syllables (2 and 3 syllables). When subjects read the cards, the correctness of reading (correct or wrong) was recorded and the degree of discomfort (from 1: no discomfort at all to 4: can't read at all) was also evaluated for all the text sizes. Results showed that the character size should be 4 pt or larger for the young subjects to read at least one word correctly in all the text conditions. For the old subjects to read at least one word correctly, the character size should be five pt or larder. The average of the minimum character sizes for 100% correct answer is 6.1 pt for young subjects and 10.5 pt for old subjects, respectively.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.295-308
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• 2021

In recent years, as many people post their interests on social media or store documents in digital form due to the development of the internet and computer technologies, the amount of text data generated has exploded. Accordingly, the demand for technology to create valuable information from numerous document data is also increasing. In this study, through statistical techniques, we investigate how the meanings of Korean words change over time by using the presidential speech records and newspaper articles public data. Using this, we present a strategy that can be utilized in the study of the synchronic change of Hangeul. The purpose of this study is to deviate from the study of the theoretical language phenomenon of Hangeul, which was studied by the intuition of existing linguists or native speakers, to derive numerical values through public documents that can be used by anyone, and to explain the phenomenon of changes in the meaning of words.

• Journal of Korea Trade
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• v.23 no.4
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• pp.58-79
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• 2019

Purpose - This study focused on the effect of mobile app information system quality on re-use intention in the medical service trade, and examined how the Chinese, currently the main consumer of Korea's medical service trade, obtained information through mobile apps, and the status of satisfaction felt by experiencing medical services. Design/methodology - The survey period was from November 2018 to January 2019, and was conducted on Chinese who voluntarily experienced medical services. The collected data verified causality of the study model through the statistical program, SPSS.24. The results showed that the most popular medical institution through the medical service mobile app is dermatology, and the quality of the app's information system plays a mediating role in influencing re-use intention. Findings - Overall, the current trade in medical services is first accessed and acquired through mobile apps, and as a result, consumers revisit medical institutions according to the reliability of information. Comments and likes, another new form of the word of mouth that has greatly influenced revisiting in the past, are seen to be spreading through the app's medical information. Originality/value - The previous market for the medical services trade was formed by very conservative word of mouth, but now we believe that the app's information system actively influences the revisit effect. This means that apps can be used in diverse areas in the medical service trade market. In addition, the medical service market needs to further develop a mobile app environment that can reflect consumers' diverse needs, behaviors, and culture from time to time in order to revitalize the service trade. Such an app environment development will have tremendous promotional effects on the trade market and provide directions for expanding trade in medical services.

• Journal of People, Plants, and Environment
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• v.24 no.5
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• pp.451-460
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• 2021

Background and objective: The prolonged COVID-19 pandemic has had significant impacts on mental health, which has emerged as a major public health issue around the world. This study aimed to analyze trends and network structure of 'grow-your-own (GYO)' through Instagram, one of the most influential social media platforms, to encourage and sustain home gardening activities for promotion of emotional support and physical health. Methods: A total of 6,388 posts including keyword hashtags '#gyo' and '#growyourown' on Instagram from June 13, 2020 to April 13, 2021 were collected. Word embedding was performed using Word2Vec library, and 7 clusters were identified with K-means clustering: GYO, garden and gardening, allotment, kitchen garden, sustainability, urban gardening, etc. Moreover, we conducted social network analysis to determine the centrality of related words and visualized the results using Gephi 0.9.2. Results: The analysis showed that various combinations of words, such as #growourrownfood, #growourrownveggies, and #growwhatyoueat revealed preference and interest of users in GYO, and appeared to encourage their activities on Instagram. In particular, #gardeningtips, #greenfingers, #goodlife, #gardeninglife, #gardensofinstagram were found to express positive emotions and pride as a gardener by sharing their daily gardening lives. Users were participating in urban gardening through #allotment, #raisedbeds, #kitchengarden and we could identify trends toward self-sufficiency and sustainable living. Conclusion: Based on these findings, it is expected that the trend data of GYO, which is a form of urban gardening, can be used as the basic data to establish urban gardening plans considering each characteristic, such as the emotions and identity of participants as well as their dispositions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.41-46
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• 2023

Recently, big data analysis can use various techniques according to the development of machine learning. Big data collected in reality lacks an automated refining technique for the same or similar terms based on semantic analysis of the relationship between words. Since most of the big data is described in general sentences, it is difficult to understand the meaning and terms of the sentences. To solve these problems, it is necessary to understand the morphological analysis and meaning of sentences. Accordingly, NLP, a technique for analyzing natural language, can understand the word's relationship and sentences. Among the NLP techniques, the transformer has been proposed as a way to solve the disadvantages of RNN by using self-attention composed of an encoder-decoder structure of seq2seq. In this paper, transformers are used as a way to form associations between words in order to understand the words and phrases of sentences extracted from big data.