• The Journal of the Acoustical Society of Korea
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• v.19 no.6
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• pp.62-70
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• 2000

In usual language models(LMs), the probability has been estimated by selecting highly frequent words from a large text side database. However, in case of adopting LMs in a specific task, it is unnecessary to using the general method; constructing it from a large size tent, considering the various kinds of cost. In this paper, we propose a construction method of LMs using a small size text database in order to be used in specific tasks. The proposed method is efficient in increasing the low frequent words by applying same sentences iteratively, for it will robust the occurrence probability of words as well. We carried out continuous speech recognition(CSR) experiments on 200 sentences uttered by 3 speakers using LMs by iterative teaming(IL) in a air flight reservation task. The results indicated that the performance of CSR, using an IL applied LMs, shows an 20.4% increased recognition accuracy compared to those without it. This system, using the IL method, also shows an average of 13.4% higher recognition accuracy than the previous one, which uses context-free grammar(CFG), implying the effectiveness of it.

• The Korean Journal of Applied Statistics
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• v.32 no.2
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• pp.301-317
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• 2019

There has been significant research conducted on how to discover various insights through text data using statistical techniques. In this study we analyzed text data produced by the Korean National Police Agency to identify trends in the work by year and compare work characteristics among local authorities by identifying distinctive keywords in documents produced by each local authority. A preprocessing according to the characteristics of each data was conducted and the frequency of words for each document was calculated in order to draw a meaningful conclusion. The simple term frequency shown in the document is difficult to describe the characteristics of the keywords; therefore, the frequency for each term was newly calculated using the term frequency-inverse document frequency weights. The L2 norm normalization technique was used to compare the frequency of words. The analysis can be used as basic data that can be newly for future police work improvement policies and as a method to improve the efficiency of the police service that also help identify a demand for improvements in indoor work.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.891-897
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• 2022

In big data analysis, raw text data mostly exists in various unstructured data forms, so it becomes a structured data form that can be analyzed only after undergoing heuristic pre-processing and computer post-processing cleansing. Therefore, in this study, unnecessary elements are purified through pre-processing of the collected raw data in order to apply the wordcloud of R program, which is one of the text data analysis techniques, and stopwords are removed in the post-processing process. Then, a case study of wordcloud analysis was conducted, which calculates the frequency of occurrence of words and expresses words with high frequency as key issues. In this study, to improve the problems of the "nested stopword source code" method, which is the existing stopword processing method, using the word cloud technique of R, we propose the use of "general stopword corpus" and "user-defined stopword corpus" and conduct case analysis. The advantages and disadvantages of the proposed "unstructured data cleansing process model" are comparatively verified and presented, and the practical application of word cloud visualization analysis using the "proposed external corpus cleansing technique" is presented.

• Smart Media Journal
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• v.12 no.11
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• pp.185-197
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• 2023

This study was conducted using text mining and network theory to extract useful information for application for occupancy and performance of permit tasks contained in the permit contents from the permit register, which is used only for the simple purpose of recording occupancy permit information. Based on text mining, we analyzed and compared the frequency of vocabulary occurrence and topic modeling in five regions, including Seoul, Gyeonggi, Gyeongsang, Jeolla, Chungcheong, and Gangwon, as well as normalization processes such as stopword removal and morpheme analysis. By applying four types of centrality algorithms, including stage, proximity, mediation, and eigenvector, which are widely used in network theory, we looked at keywords that are in a central position or act as an intermediary in the network. Through a comprehensive analysis of vocabulary appearance frequency, topic modeling, and network centrality, it was found that the 'installation' keyword was the most influential in all regions. This is believed to be the result of the Ministry of Environment's permit management office issuing many permits for constructing facilities or installing structures. In addition, it was found that keywords related to road facilities, flood control facilities, underground facilities, power/communication facilities, sports/park facilities, etc. were at a central position or played a role as an intermediary in topic modeling and networks. Most of the keywords appeared to have a Zipf's law statistical distribution with low frequency of occurrence and low distribution ratio.

• Journal of the Korean Society for information Management
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• v.28 no.4
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• pp.65-83
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• 2011

In this study, Network Text Analysis was performed on 1,752 articles which had been published in recent 7 years and drew the subject concept distribution and their relations in Library and Information Science research areas. Furthermore, for analyzing more recent trends and changing aspects, this study performed secondary analysis based on 482 articles published in recent 2 years. Results show that "public library", and "academic library" concepts were most frequently studied in the field and "evaluation", "education", and "web" concepts showed the highest-degree centrality during the recent 7 years. In the result of recent two years analysis, "web", and "classification" concepts showed high frequency and "user", and "public library" showed an improvement in high degree centrality.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1593-1598
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• 2015

In this paper, we analyze the correlation between social sentiment and stock prices. Polarity analysis is conducted for the stock prices plunging and soaring duration. And it is performed for its prior period. Using these results, we analyze the relationship between the social sentiment and stock prices. We collected the past data of Dow Jones Industrial Average and detected the period of plunging and soaring. On the basis of the detected time, the New York Times articles are collected and polarity analysis is conducted. Frequency of negative terms is decreased and it of positive terms is increased during the stock prices soaring. There is a little difference between the frequency of negative and positive terms in the previous stock prices plunging or soaring. According to the correlation analysis, it shows a positive correlation between social sentiment and stock prices in the period of plunging and soaring. A significant correlation is not appeared in the previous stock prices plunging or soaring.

• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.1-9
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• 2018

Drug repositioning is to discover new uses of drugs. Text mining derives knowledge from unstructured text. We propose a method to predict new drug-disease relationships by taking into account the rate of frequency of genes simultaneously measured in disease-gene and gene-drug. Co-occurrence of drug-gene and gene-disease in the biological literature is counted and calculate the rate of the gene for each drug and disease. Weights of drug-disease relationships are calculated using the average of the rates of genes that are measured and used to measure the accuracy for each disease. In measuring drug-disease relationships, a more accurate identification of relationships was shown by measuring the frequency on a sentence and considering multiple relationships than existing method.

• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.146-151
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• 2019

This study performed to identify the relationship between job stress and self-efficacy based on the related research review and text network analysis. For the literature review, we performed the search process at three domestic and one foreign database using key words, 'nurse', 'stress', 'self-efficacy'. A total of 18 papers were selected as the target literature. Nine of these studies reported a statistically significant negative correlation between nurses' job stress and self-efficacy. It was difficult to compare between studies' results because of the optional usage of the questionnaires. In addition, a text network analysis was conducted by extracting keywords from the 18 papers. The keyword with the highest frequency of appearance was job stress, and the main words with high frequency of emergence were self-efficacy, hospital, and correlation. To clarify the relationship between the keywords, it is proposed to perform a survey on the influence factors through the development of Korean version measurement.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.429-429
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• 2023

우리나라의 물 관련 정책 방향이 환경 중심의 수자원 관리에서 친수공간 및 정보의 확보와 같은 안전한 물관리로 확대되면서 정책추진에 기초가 될 수 있는 신뢰도 높은 수문자료의 생산이 보다 중요시되고 있다. 국가 수문조사사업은 이러한 정책기조에 맞춰 제도적인 뒷받침과 함께 조사의 범위와 기술, 품질관리 등의 영역을 넓히며 그 기능을 활발히 하고 있으나, 물관리 정책의 경향에 따른 수문조사사업의 방향성과 특징을 구조적으로 살펴본 연구는 부족한 것으로 파악된다. 따라서 본 연구는 친수·친환경적 물관리가 강조된 시기('97~현재)를 중점으로 하여 물관리 정책과 관련 계획의 변화가 수문조사사업에 어떠한 영향을 주는지 고찰하였다. 이를 위해 물관리 여건의 변화에 따라 달라진 관련 정책별 주제어의 분포와 수문조사사업과 연관된 주요어의 출현빈도 및 경향을 살펴보고, 주요 연관어와 연계한 사업의 방향과 구조를 분석하였다. 분석자료로는 물관리 관련 법령 등의 제도와 언론기사자료, 정책별 추진방향을 활용하였다. 정책의 추진방향은 1) 수자원의 종합적 개발에서 친환경적 측면과 지속가능성이 강조된 수자원장기종합계획(3-1차~4-3차)과 2) 사람과 자연이 함께 고려된 맑고 안전한 물, 통합물관리 등의 전략이 수록된 국가물관리기본계획(1차), 3) 정책의 기조에 따라 수립 및 보완된 수문조사 기본계획(1~2차)을 바탕으로 하였다. R프로그램을 통한 텍스트 마이닝을 활용하여 각 자료에서의 주제어 분포와 출현빈도를 분석하고, 정책별 추진방향과 수문조사사업의 연계성을 나타내었다. 연구의 함의를 담은 결과로서 물관리 여건이 변화된 시점별 주요연관어를 중심으로 한 정책동향과 수문조사사업의 특징 및 방향을 요약·비교하여 제시하였으며, 이는 물관리 분야에서의 국정운영 목표와 연계하여 국가 수문조사사업의 사업성을 고찰하는 연구의 기반이 될 수 있으리라 생각된다.

• Journal of the Korean Society for information Management
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• v.31 no.1
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• pp.99-118
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• 2014

This paper carried out co-word analysis of noun and noun phrase using text-mining technique in order to grasp the research trends on domestic and international information science articles. It was conducted based on collected titles and articles of the papers published in the Journal of the Korean Society for Information Management (KOSIM) and Journal of American Society for Information Science and Technology (JASIST) from 1990 to 2013. By dividing whole period into five publication window, this paper was organized into the following processes: 1) analysis of high frequency co-word pair to examine the overall trends of both information science articles 2) analysis of each word appearing with high frequency keyword to grasp the detailed subject 3) focused network analysis of trend after 2010 when distinctively new keyword appeared. The result of the analysis shows that KOSIM has considerable portion of studies conducted regarding topics such as library, information service, information user and information organization. Whereas, JASIST has focused on studies regarding information retrieval, information user, web information, and bibliometrics.