• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.55-65
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• 2023

In this paper, we apply KeyBERT(Keyword extraction with Bidirectional Encoder Representations of Transformers) algorithm-driven topic extraction and topic frequency analysis to deep learning and reinforcement learning research to discover the rapidly changing trends in them. First, we crawled abstracts of research papers on deep learning and reinforcement learning, and temporally divided them into two groups. After pre-processing the crawled data, we extracted topics using KeyBERT algorithm, and then analyzed the extracted topics in terms of topic occurrence frequency. This analysis reveals that there are distinct trends in research work of all analyzed algorithms and applications, and we can clearly tell which topics are gaining more interest. The analysis also proves the effectiveness of the utilized topic extraction and topic frequency analysis in research trend analysis, and this trend analysis scheme is expected to be used for research trend analysis in other research fields. In addition, the analysis can provide insight into how deep learning will evolve in the near future, and provide guidance for select research topics and methodologies by informing researchers of research topics and methodologies which are recently attracting attention.

• The KIPS Transactions:PartA
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• v.12A no.2 s.92
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• pp.109-116
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• 2005

In this paper, we introduce the method that a user analyses the similarity of the two programs by using keyword from the syntactic tree, created after the syntax analysis, and its implementation. The main advantage of the method is the performance improvement through using only keyword of syntax tree. In the paper, we propose the similarity evaluation model and how we extract keyword from syntax tree. In addition, we also show the improvement in the performance in analysis and in the system's structure. We expect that our system will be utilized in the similarity evaluation in text and XML documents.

• Journal of the Korean Society for Library and Information Science
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• v.33 no.2
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• pp.119-139
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• 1999

It Is the purpose of this research to analyse users' understanding how keyword and boolean search work in SELIS(SEoul Women's University Library and Information System) OPAC. Results of analyses of the subject, SELIS OPAC system processing, are: comprehension percentage of keyword extraction is $67(22.48\%)$ out of total 298 persons, no comprehension is $231(77.52\%)$ understanding of boolean OR In keyword search appears $115(22.48\%)$ out of 297, no understanding does $182(77.52\%)$ : comprehension of boolean AND is $98(33.11\%)$ out of 296, no understanding appears $198(66.89\%)$ understanding of using boolean and symbols is $109(36.49\%)$ out of 285, no understanding is $181(63.51\%)$ which Is lower percentage generally. And in SELIS OPAC system, in Intentional analyses to see any difference in understanding of keyword search between experience of keyword search or no, It shows no difference in interrelation $5\%$ level of significance, but In boolean search it does in interrelation $5\%$ level of significance.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06a
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• pp.1-2
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• 2008

• Journal of Information Technology Services
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• v.19 no.3
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• pp.117-137
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• 2020

The development of information technology leads to changes in various industries. In particular, the health care industry is more influenced so that it is focused on. With the widening of the health care market, the market of smart device based personal health care also draws attention. Since a variety of fitness applications for smartphone based exercise were introduced, more interest has been in the health care industry. But although an amount of use of mobile fitness applications increase, it fails to lead to a sustained use. It is necessary to find and understand what matters for mobile fitness application users. Therefore, this study analyze the reviews of mobile fitness application users, to draw key factors, and thereby to propose detailed strategies for promoting mobile fitness applications. We utilize text mining techniques - LDA topic modeling, term frequency analysis, and keyword extraction - to draw and analyze the issues related to mobile fitness applications. In particular, the key factors drawn by text mining techniques are explained through the concept of user experience. This study is academically meaningful in the point that the key factors of mobile fitness applications are drawn by the user experience based text mining techniques, and practically this study proposes detailed strategies for promoting mobile fitness applications in the health care area.

• Journal of the Korean Society for information Management
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• v.36 no.4
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• pp.7-19
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• 2019

The aim of this study is to develop a technique for keyword extraction in Korean-Chinese text in the modern period. We considered a Korean morphological analyzer and a particle in classical Chinese as a possible method for this study. We applied our method to the journal "Sisachongbo," employing proper-noun dictionaries and a list of stop words to extract index terms. The results show that our system achieved better performance than a Chinese morphological analyzer in terms of recall and precision. This study is the first research to develop an automatic indexing system in the traditional Korean-Chinese mixed text.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.5
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• pp.80-86
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• 2010

This paper presents automated music story video generation technique as one of entertainment features that is equipped in multimedia system of the vehicle. The automated music story video generation is a system that automatically creates stories to accompany musics with photos stored in user's mobile phone by connecting user's mobile phone with multimedia systems in vehicles. Users watch the generated music story video at the same time. while they hear the music according to mood. The performance of the automated music story video generation is measured by accuracies of music classification, photo classification, and text-keyword extraction, and results of user's MOS-test.

• Journal of the Korea Society of Computer and Information
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• v.5 no.2
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• pp.14-21
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• 2000

In the position of the users, it suggests the technology information space as a now paradigm, which supplement the function of science information DB. ICPIS which inputs described papers with keywords, offers the itemized summary of these contents, the visual indication and comparison of similar thesis. and it also supplises the abundant summary information, survey information, more than ten volumes of info communication thesis with starting the casual relation extraction for the users, playing a significant role in ICPIS is called KP, and it is package of domain knowledge that unifies the extraction and structure narration of the technology information. ICPIS extracts the technology information among the thesis that are deserved by the natual language treatment in the itemized KP described , and form the prescribed summary structure in KP.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.595-602
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• 2008

The focused word of each sentence is a help in recognizing and understanding spoken Korean. To find the method of focused word spotting at spoken speech signal, we made an analysis of the average and variance of Fundamental Frequency and the average energy extracted from a focused word and the other words in a sentence by experiments with the speech data from 100 spoken sentences. The result showed that focused words have either higher relative average F0 or higher relative variances of F0 than other words. Our findings are to make a contribution to getting prosodic characteristics of spoken Korean and keyword extraction based on natural language processing.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.377-381
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• 2008

Chinease-Korean Cultural Map, which is an electronic cultural map that shows Chinese-Korean culture on maps, is planned as the first step to development Asian Electronic Cultural Map. Chinese-Korean have their unique cultural characteristics same as other small tribes. Small tribes shows same typical cultural characteristics of Asian, and that characteristics are very important factors for understanding the whole Asian culture. This paper proposes a logical and standardized development methodology for construction of Electronic Cultural Map. The methodology consists of 6 steps; information analysis, keyword extraction, keyword clustering, map element extraction, prototype design, and map development. We used and evaluated the methodology during prototype design and development steps for the optimal functions. To generate the base maps for Chinese-Korean Cultural Map, we use Google Earth and KML(Keyhole Markup Language) for standardized and easy development.