• The Journal of the Acoustical Society of Korea
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• v.19 no.2E
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• pp.27-31
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• 2000

Evaluating log-likelihood of Gaussian mixture density is major computational burden for the keyword spotting system using continuous HMM. In this paper, we employ the bucket box intersection (BBI) algorithm to reduce the computational complexity of keyword spotting. We make some modification in implementing BBI algorithm in order to increase the discrimination ability among the keyword models. According to our keyword spotting experiments, the modified BBI algorithm reduces 50% of log-likelihood computations without performance degradation, while the original BBI algorithm under the same condition reduces only 30% of log-likelihood computations.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.91-98
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• 2019

The present study was performed to investigate the general research trends of dyslexia and learning disability to explore the centrality of related variables though analysis of keyword networks. Data were collected from ten years articles research information sharing service(RISS) which is provided by korea education and research information service(KERIS). The research subjects selected for the analysis were keyword cleansing work, extraction major keyword using KrKwic program and using NodeXL program to Visualize the center of connection between keyword. The results of this were as follows. First, totally 72 of keyword were extracted from keyword cleansing process and among those keyword. major keywords included learning disability, dyslexia, RTI. Second, analysis of the betweenness centrality of dyslexia and learing disabilities shows that learning disabilities are a key word that has been addressed in the study of dyslexia and learning disabilities in korea. The results of these studies suggest a method of analyzing trends in qualitative and qualitative analysis in relation to dyslexia and learning disorder.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.17-24
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• 2018

One of the major issues in big data processing is extracting keywords from internet and using them to process the necessary information. Most of the proposed keyword extraction algorithms extract keywords using search function of a large portal site. In addition, these methods extract keywords based on already posted or created documents or fixed contents. In this paper, we propose a KAES(Keyword Advertisement Extraction System) system that helps the potential shopping keyword marketing to extract issue keywords and related keywords based on dynamic instant messages such as various issues, interests, comments posted on SNS. The KAES system makes a list of specific accounts to extract keywords and related keywords that have most frequency in the SNS.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.177-178
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• 2019

본 연구는 지방교육자치의 가장 핵심인 '교육감' 관련 연구들의 주요 핵심어들과 그들 간의 관계성을 분석하였다. 본 연구에서는 2009년부터 2018년까지(10년간)의 '교육감' 관련 선행연구 총 93건을 키워드 네트워크 분석 방법론을 활용하여, 주요 핵심어 추출 및 워드 클라우드 제시, 주요 핵심어들 간의 관계성(의미망 네트워크) 분석 등을 진행하였다. 최근 10년간 국내 '교육감' 관련 연구들의 주요 핵심어들은 교육감선거, 주민직선제, 선출제도, 개선방안, 비교연구, 교육자치, 문제점, 지방자치, 교육부장관, 교육위원 등 이었다. 주요 핵심어들(상위 출현빈도)은 높은 밀도와 연결정도를 가지고 상호 네트워크를 형성하고 있었다. 본 연구결과는 향후 진행될 '교육감' 관련 후속연구들의 새로운 연구주제 선정 및 다양한 방향 설정에 기초자료로 활용될 수 있을 것이다.

• Journal of the Korea Society of Computer and Information
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• v.24 no.7
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• pp.135-141
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• 2019

The purpose of this study is to extract the key words from the list of research subjects related to 'hotel workers' published in recent 10 years(2009~2018) by using the language network analysis method and to confirm the relation between the key words. In this paper, we propose a semantic network analysis that can overcome limitations of longitudinal study, analyze the recent research trends, and widely use as a research model. The results of this study are as follows ; First, in analyzing major key words in the title of 'Hotel Employer' in recent 10 years, the major keyword of job satisfaction(40), special grade(26), organizational commitment(20), emotional labor(19), service(12), restaurant(10), and turnover intention(9). Second, we analyzed the relation of language network among major key words extracted from the study title of 'hotel workers'. Such a research process is expected to grasp the trends of research related to 'hotel workers' and give implications for the future direction of related research.

• Journal of Information Processing Systems
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• v.5 no.3
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• pp.159-166
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• 2009

As shown in Wikipedia, tagging or cross-linking through major keywords in a document collection improves not only the readability of documents but also responsive and adaptive navigation among related documents. In recent years, the Semantic Web has increased the importance of social tagging as a key feature of the Web 2.0 and, as its crucial phenotype, Tag Cloud has emerged to the public. In this paper we provide an efficient method of automated in-text keyword tagging based on large-scale controlled term collection or keyword dictionary, where the computational complexity of O(mN) - if a pattern matching algorithm is used - can be reduced to O(mlogN) - if an Information Retrieval technique is adopted - while m is the length of target document and N is the total number of candidate terms to be tagged. The result shows that automatic in-text tagging with keywords filtered by Information Retrieval speeds up to about 6 $\sim$ 40 times compared with the fastest pattern matching algorithm.

• Transactions of the Korean hydrogen and new energy society
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• v.33 no.2
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• pp.130-141
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• 2022

Due to continuous climate change, greenhouse gases in the atmosphere are gradually accumulating, and various extreme weather events occurring all over the world are a serious threat to human sustainability. Countries around the world are making efforts to convert energy sources from traditional fossil fuels to renewable energy. Hydrogen energy is a clean energy source that exists infinitely on Earth, and can be used in most areas that require energy, such as power generation, transportation, commerce, and household sectors. A fuel cell, a device that produces electric and thermal energy by using hydrogen energy, is a key field to respond to climate change, and major countries around the world are spurring the development of core fuel cell technology. In this paper, research trends in China, the United States, Germany, Japan, and Korea, which have the highest number of papers related to fuel cells, are analyzed through keyword network analysis.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.859-870
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• 2009

Despite the surge in the research for keyword search method over relational database, only little attention has been devoted to studying on relational data stream.The research for keyword search over relational data stream is intense interest because streaming data is recently a major research topic of growing interest in the data management. In this regard we first analyze the researches related to keyword search methodover relational data stream, and then this paper focuses on the method of minimizing the join cost occurred while processing keyword search queries. As a result, we propose an advanced keyword search method that can yield more meaningful results for users on relational data streams. We also propose a query optimization method using layered-clustering for efficient query processing.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.1
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• pp.157-169
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• 2015

In digital marketing, means of public relations and marketing of enterprises are changing into marketing techniques of predictive analytics. A significant study can be carried out by an analysis of 'the patterns of customers' uses' using big data on major portal sites and SNSs and their correlation with related keywords. This study analyzes the origins of mythological characters in major brands such as Nike, Hermes, Versace, Canon and Starbucks. Also, it extracts related keywords and relevance using big data on portal sites and SNS and their correlation. Nike marketing that reminds people of 'the goddess of victory, Nike' formed a good combination of the brand with relevance. Most of them are based on Greek mythology and have rich materials for storytelling and artistic values in common. Hopefully, this case analysis of foreign brands would become a starting point of discovering the materials of the domestic mythological characters.

• Korea Trade Review
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• v.45 no.5
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• pp.239-260
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• 2020

This research was conducted on 176 GVCs-related research papers listed in the Index of Korean Academic Writers. The analysis methodology used the keyword network analysis methodology of big data analysis. For the comprehensive analysis of research trends, the research trends through word frequency (TF), important topic (TF-IDF), and topical modeling were analyzed in 176 papers. In addition, the research period of GVCs was divided into the early stages of the first study (2003-2014), the second phase of the study (2015-2017), and the third phase of the study (2018-2020). According to the comprehensive analysis, the GVCs research was conducted with the keyword 'value added' as the center, focusing on the keywords of export (trade), Korea, business, influence, and production. Major research topics were 'supporting corporate cooperation and capacity building' and 'comparative advantage with added value of overseas direct investment'. According to the analysis of major period-specific research trends, GVCs were studied in the early stages of the first phase of the study with global value chain trends and corporate production strategies. In the second research propulsion period, research was done in terms of trade value added. In the recent third phase of the study, small and medium-sized enterprises actively participated in the global value chain and actively researched ways to support the government. Through this study, the importance of the global value chain has been confirmed quantitatively and qualitatively, and it is recognized as an important factor to be considered in the strategy of enhancing industrial competitiveness and entering overseas markets. In particular, small and medium-sized companies' participation in the global value chain and support measures are being presented as important research topics in the future.