• Asian Journal of Innovation and Policy
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• v.12 no.3
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• pp.304-322
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• 2023

Text data mining ('big data methods') is one of the most widely used approaches during the COVID-19 pandemic. In particular, text data mining on Scopus databases or Web of Science (WoS). Text data mining is widely used to collect literature for later bibliometric analysis, and in the end, it becomes a literature review article. Therefore, in this article, we reveal the trend of publication of literature reviews in Scopus journals from Indonesia, Japan, South Korea, Vietnam, Singapore, and Malaysia. This article describes two essential parts, namely 1) a comparison of international publication trends and subject area of literature review publications, and 2) a comparison of Top 5 for Authors, Affiliation, Source Title, and Collaboration Country.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.221-226
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• 2024

This study used text mining, a big data analysis technique, to explore XR trends in South Korea. For this research, I utilized a big data platform called BigKinds. I collected data focusing on the keyword 'XR', spanning approximately 14 years from 2010 to 2024. The gathered data underwent a cleansing process and was analyzed in three ways: keyword trend analysis, relational analysis, and word cloud. The analysis identified the emergence and most active discussion periods of XR, with XR devices and manufacturers emerging as key keywords.

• Journal of Information Management
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• v.33 no.2
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• pp.19-32
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• 2002

With the growth of the digital library and the use of Internet, the amount of online text information has increased rapidly. The need for efficient data management and retrieval techniques has also become greater. An automatic text categorization system assigns text documents to predefined categories. The system allows to reduce the manual labor for text categorization. In order to classify text documents, the good features from the documents should be selected and the documents are indexed with the features. In this paper, each steps of text categorization and several techniques used in each step are introduced.

• Asia pacific journal of information systems
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• v.32 no.4
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• pp.770-802
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• 2022

With the development of deep learning techniques, text mining is producing breakthrough performance improvements, promising future applications, and practical use cases across many fields. Likewise, even though several attempts have been made in the field of financial information, few cases apply the current technological trends. Recently, companies and government agencies have attempted to conduct research and apply text mining in the field of financial information. First, in this study, we investigate various works using text mining to show what studies have been conducted in the financial sector. Second, to broaden the view of financial application, we provide a description of several text mining techniques that can be used in the field of financial information and summarize various paradigms in which these technologies can be applied. Third, we also provide practical cases for applying the latest text mining techniques in the field of financial information to provide more tangible guidance for those who will use text mining techniques in finance. Lastly, we propose potential future research topics in the field of financial information and present the research methods and utilization plans. This study can motivate researchers studying financial issues to use text mining techniques to gain new insights and improve their work from the rich information hidden in text data.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1259-1269
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• 2015

Recently, big data is positioning as a keyword in the academic circles. And usefulness of big data is carried into government, a local public body and enterprise as well as academic circles. Also they are endeavoring to obtain useful information in big data. This research mainly deals with analyses of box office success or failure of films using text mining. For data, it used a portal site 'D' and film review data, grade point average and the number of screens gained from the Korean Film Commission. The purpose of this paper is to propose a model to predict whether a film is success or not using these data. As a result of analysis, the correct classification rate by the prediction model method proposed in this paper is obtained 95.74%.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1281-1281
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• 2024

About 70% of the data generated on building construction sites consists of unstructured data, such as text, photos, videos, etc. However, the text data, which constitutes the largest proportion of unstructured data, has been restrictively utilized. When using standardized data to evaluate safety performance, there are a few difficulties in addressing issues such as lack of data, omissions, and errors. This copes with limitations on the practical evaluation of safety performance on building construction sites. Despite generating extensive text-centric documents, the previous researches on evaluating safety performance levels using unstructured data are still in its infancy. This study proposes a framework for evaluating the safety performance by preprocessing and refining text-based construction supervision documents. In this framework, relevant keywords related to safety performance are extracted from supervision documents, tokenized, and analyzed for association rules among keywords. Based on the results of the association rule analysis, keywords are selected, and the unsatisfactory or satisfactory level of safety performance is quantified using logistic regression analysis, considering the frequency of their occurrence. While the proposed framework focuses on quantifying the safety performance levels of construction sites, it can be expanded to implement integrated performance diagnostics on-site by linking with tools that evaluate diverse performance levels. This extension will allow for a comprehensive assessment of on-site performance. Furthermore, the framework can serve as a tool supporting practical and proactive inspections and responses of safety managers by utilizing unstructured data alongside the traditional approach focused on standardized data for safety performance assessment.

• Culinary science and hospitality research
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• v.24 no.2
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• pp.34-43
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• 2018

The objective of this study was to acquire a general and text-based awareness and recognition of cruise food hygiene through big data analytics. For the purpose, this study collected data with conducting the keyword "food hygiene, cruise" on the web pages and news on Google, during October 1st, 2015 to October 1st, 2017 (two years). The data collection was processed by SCTM which is a data collecting and processing program and eventually, 899 kb, approximately 20,000 words were collected. For the data analysis, UCINET 6.0 packaged with visualization tool-Netdraw was utilized. As a result of the data analysis, the words such as jobs, news, showed the high frequency while the results of centrality (Freeman's degree centrality and Eigenvector centrality) and proximity indicated the distinct rank with the frequency. Meanwhile, as for the result of CONCOR analysis, 4 segmentations were created as "food hygiene group", "person group", "location related group" and "brand group". The diagnosis of this study for the food hygiene in cruise industry through big data is expected to provide instrumental implications both for academia research and empirical application.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.30 no.1
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• pp.19-28
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• 2018

Numerous research papers have been accumulated due to the development and computerization of bibliometrics. This made it difficult to review all of the related papers published worldwide to conduct the study. However, due to the development of Natural language processing techniques, the tendency analysis of published research papers has become easier. In this study, text mining analysis using the statistical computing language R was carried out based on the bibliographic information of SCOPUS DB (Data Base) in the field of coastal and ocean engineering. As expected, the term 'wave' predominates, and it was confirmed that numerical analysis and hydraulic experiments were still dominant from the terms 'numerical model', 'numerical simulation', and 'experimental study'. In addition, recent use of the term 'wave energy' related to marine energy has been recognized. On the other hand, it was quantitatively confirmed that the frequency of connection between 'wave', and 'height' or 'energy' prevailed, and suggested the possibility of high resolution analysis by detailed field and period in the future.

• Journal of Sport and Applied Science
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• v.3 no.2
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• pp.17-27
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• 2019

Purpose: This study is to conduct usability evaluations from the perspective of developing comfort-shoes for the middle-aged and elderly to identify key factors and derive implications for optimal comfort-shoes production. Research design, data, and methodology: A total of 10 middle-aged and elderly women in their 50s and 60s were selected as eligible for the rescue. For data collection, the study was conducted in a Gang Survey, where pre-explanations, shoes test, and interviews were conducted. The collected data were analyzed in a total of four stages. In step 1, the contents obtained through interviews with the subjects were recorded in text, organized and analyzed systematically, and in step 2, unnecessary vocabulary, sentences, and overlapping opinions were eliminated. In step 3, we classified areas around key functions and carried out categorization tasks. Finally, in Step 4, the results and implications of the study were derived by classifying each usability evaluation shoe as positive and negative text around categorized data. Results: There are a total of seven factors for comfort-shoes usability evaluation, which are categorized as cushion, fitting, stability, flexibility, lightweight, comfort, and pressure. Positive/negative factors for the derived usability evaluation factors were shown in the form of a positive-centered, negative-centered, and positive-mixed mix for each of the four products. Positive-focused products are VA products, which are seven times more positive than negative factors. Negative-centered products are CL and SA products, which are five times more negative than positive factors. Positive mixing was a CA product with a ratio of 1:1. Text-based usability evaluations allow us to proceed with analysis based on more scientific data rather than simply listening to opinions and judging by comments. Conclusions: The study discussed implications of developing comfort-shoes for middle-aged consumers and future directions were discussed.

• Smart Media Journal
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• v.12 no.11
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• pp.77-85
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• 2023

After COVID-19, communication through online platforms has increased, leading to an accumulation of massive amounts of conversational text data. With the growing importance of summarizing this text data to extract meaningful information, there has been active research on deep learning-based abstractive summarization. However, conversational data, compared to structured texts like news articles, often contains missing or transformed information, necessitating consideration from multiple perspectives due to its unique characteristics. In particular, vocabulary omissions and unrelated expressions in the conversation can hinder effective summarization. Therefore, in this study, we restructured by considering the characteristics of Korean conversational data, fine-tuning a pre-trained text summarization model based on KoBART, and improved conversation data summary perfomance through a refining operation to remove redundant elements from the summary. By restructuring the sentences based on the order of utterances and extracting a central speaker, we combined methods to restructure the conversation around them. As a result, there was about a 4 point improvement in the Rouge-1 score. This study has demonstrated the significance of our conversation restructuring approach, which considers the characteristics of dialogue, in enhancing Korean conversation summarization performance.