• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.365-372
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• 2021

The purpose of this study was to examine the statements characteristics of the pressure ulcer nursing record by natural langage processing and assess the prediction accuracy for each pressure ulcer stage. Nursing records related to pressure ulcer were analyzed using descriptive statistics, and word cloud generators (http://wordcloud.kr) were used to examine the characteristics of words in the pressure ulcer prevention nursing records. The accuracy ratio for the pressure ulcer stage was calculated using deep learning. As a result of the study, the second stage and the deep tissue injury suspected were 23.1% and 23.0%, respectively, and the most frequent key words were erythema, blisters, bark, area, and size. The stages with high prediction accuracy were in the order of stage 0, deep tissue injury suspected, and stage 2. These results suggest that it can be developed as a clinical decision support system available to practice for nurses at the pressure ulcer prevention care.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.24-33
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• 2021

This study examined a semantic relationship expressed in college presidents' welcome greetings in order to explore the promotion strategies and future direction of universities in Daegu & Gyeongbuk provinces in South Korea. Greetings were collected from university websites as of September, 2020. According to word frequency analysis, "everyone," "welcome," and "visiting" were mostly used in the headlines. In the body texts, "college" and "education" were frequently paired. While the two- & three-year colleges focus on industrial and technical capabilities, four-year universities tend to emphasize educational excellence and academic research performance. This study is valuable in that it understands the direction that universities in Daegu and North Gyeongsang Province put forward amid the decreasing school-age population and the changing social environment.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.41-47
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• 2019

It is very important to search for and obtain an example of a similar judgment in case of court judgment. The existing judge's document search uses a method of searching through key-words entered by the user. However, if it is necessary to input an accurate keyword and the keyword is unknown, it is impossible to search for the necessary document. In addition, the detected document may have different contents. In this paper, we want to improve the effectiveness of the method of vectorizing a document into a three-dimensional space, calculating cosine similarity, and searching close documents in order to search an accurate judge's example. Therefore, after analyzing the similarity of words used in the judge's example, a method is provided for extracting the mode and inserting it into the text of the text, thereby providing a method for improving the cosine similarity of the document to be retrieved. It is hoped that users will be able to provide a fast, accurate search trying to find an example of a tax-related judge through the proposed model.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.187-195
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• 2019

The purpose of this study is to investigate the effect of tourism councils on the activation of rural tourism by comparing the rural tourism sites with the tourism councils and the rural tourism sites without tourism councils. The comparative indicators were divided into statistical quantitative indicators such as number of tourists, sales volume, and income level, and qualitative indicators of satisfaction, return visit, and word of mouth intentions. As a result of the study, it was found that all the items of the quantitative and qualitative indicators were active in the rural tourism area where the tourism council was composed. This can be attributed to the fact that the members of the tourism council consist of administrative agencies, experts, tourism operators, experts, etc., and constantly develop strategic programs such as diverse opinions and unique constellations. Therefore, in order to revitalize rural tourism in the future, it can be said that the tourism council should be constructed, and institutional devices should be prepared so that experts and residents in each field can participate equally.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.8
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• pp.343-348
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• 2019

In recent years, extractive summarization systems based on end-to-end deep learning models have become popular. These systems do not require human-crafted features and adopt data-driven approaches. However, previous related studies have shown that linguistic analysis features such as part-of-speeches, named entities and word's frequencies are useful for extracting important sentences from a document to generate a summary. In this paper, we propose an extractive summarization system based on deep neural networks using conventional linguistic analysis features. In order to prove the usefulness of the linguistic analysis features, we compare the models with and without those features. The experimental results show that the model with the linguistic analysis features improves the Rouge-2 F1 score by 0.5 points compared to the model without those features.

• Phonetics and Speech Sciences
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• v.11 no.3
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• pp.39-47
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• 2019

We propose a method to improve the performance of spontaneous speech recognizers by extending their phone set using speech data. In the proposed method, we first extract variable-length phoneme-level segments from broadcast speech signals, and convert them to fixed-length latent vectors using an long short-term memory (LSTM) classifier. We then cluster acoustically similar latent vectors and build a new phone set by choosing the number of clusters with the lowest Davies-Bouldin index. We also update the lexicon of the speech recognizer by choosing the pronunciation sequence of each word with the highest conditional probability. In order to analyze the acoustic characteristics of the new phone set, we visualize its spectral patterns and segment duration. Through speech recognition experiments using a larger training data set than our own previous work, we confirm that the new phone set yields better performance than the conventional phoneme-based and grapheme-based units in both spontaneous speech recognition and read speech recognition.

• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.646-657
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• 2019

It has been 20 years since the cultural contents were newly emerged in the late 1990s and grown in our society. However, efforts to establish culture contents concept and to establish cultural contents as a separate discipline are relatively poor. There may be various reasons, but the most important thing is that it failed to cover the broad sense of the word 'cultural contents' and to present a key concept through the core. Therefore, this study examined the possibility of securing the conceptual resources necessary to lay the foundation for cultural contents within play, under the premise that cultural contents should be play studies in the 21st century. In order to do this, this paper examined the meaning of play in each of the three conceptual categories, ie, mimesis, aesthetics, and power, which are deemed to be related to the meaning of cultural contents that we currently use. As a result, it has been confirmed that play is used in various ways in connection with various concepts such as emotion, art, percept, cognition, education, coincidence, power, hegemony, class, religion, ritual. These various uses of play concept can give cultural contents researchers an opportunity to study cultural contents from a play perspective.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.3
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• pp.237-246
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• 2019

In order to improve the accuracy of the rating prediction of the recommendation model, not only user-item rating data are used but also consider auxiliary information of item such as comments, tags, or descriptions. The traditional approaches use a word-level model of the bag-of-words for the auxiliary information. This model, however, cannot utilize the auxiliary information effectively, which leads to shallow understanding of auxiliary information. Convolution neural network (CNN) can capture and extract feature vector from auxiliary information effectively. Thus, this paper proposes character-level deep-Convolution Neural Network based matrix factorization (Char-DCNN-MF) that integrates deep CNN into matrix factorization for a novel recommendation model. Char-DCNN-MF can deeper understand auxiliary information and further enhance recommendation performance. Experiments are performed on three different real data sets, and the results show that Char-DCNN-MF performs significantly better than other comparative models.

• The Korean Journal of Archival Studies
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• no.34
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• pp.165-219
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• 2012

Folklife archival science(folklife: Folklore is generally used in Engish-speaking countries but it has a strong meaning as remnants of former times. That's why I am useing the term-folklife instead of folklore in this paper. I think folklife is more appropriate term for expressing studies on daily life culture and also my intention to unite the both word in this paper) is a new academic movement, I propose, which is intended on convergence of advantage of folklife and archival science. In other words, taking advantage of the two branches of study(folklife, archival science), it becomes a practical studies which systematically organize records, preservations and application on living culture in any community. It demonstrate deeply on archiving and archive and It conducts a probe into records, preservations and applications. It is a method of technical study in order to record communities like village, rural society and modern city. In the mean time, there is no well defined and established methodology for archival science and for folk-area or community archiving. And therefore, It needs a research methodology in a folklife. In the other hand, there is a lack of a theoretical basis, methodological strategy and clear vision over folklife and field survey or method of survey. Therefore, converging advatage of the two studies(folklife, archival science), we can combine professionalism of community archiving and methodological strategy together.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.1-8
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• 2019

Among the methods for extracting the most appropriate information from a large amount of log data, there is a method using inductive inference. In this paper, we use SVM (Support Vector Machine), which is an excellent classification method for inductive inference, in order to determine the ranking of intrusion logs in digital forensic analysis. For this purpose, the logs of the training log set are classified into intrusion logs and normal logs. The associated words are extracted from each classified set to generate a related word dictionary, and each log is expressed as a vector based on the generated dictionary. Next, the logs are learned using the SVM. We classify test logs into normal logs and intrusion logs by using the log set extracted through learning. Finally, the recommendation orders of intrusion logs are determined to recommend intrusion logs to the forensic analyst.