• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• Knowledge Management Research
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• v.21 no.1
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• pp.197-210
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• 2020

The smart speaker includes an AI assistant function in the existing portable speaker, which enables a person to give various commands using a voice and provides various offline services associated with control of a connected device. The speed of domestic distribution is also increasing, and the functions and linked services available through smart speakers are expanding to shopping and food orders. Through text mining-based customer review analysis, there have been many proposals for identifying the impact on customer attitudes, sentiment analysis, and product evaluation of product functions and attributes. Emotional investigation has been performed by extracting words corresponding to characteristics or features from product reviews and analyzing the impact on assessment. After obtaining the topic from the review, the effect on the evaluation was analyzed. And the market competition of similar products was visualized. Also, a study was conducted to analyze the reviews of smart speaker users through text mining and to identify the main attributes, emotional sensitivity analysis, and the effects of artificial intelligence attributes on product satisfaction. The purpose of this study is to collect blog posts about the user's experiences of smart speakers released in Korea and to analyze the attitudes of customers according to their attributes. Through this, customers' attitudes can be identified and visualized by each smart speaker product, and the positioning map of the product was derived based on customer recognition of smart speaker products by collecting the information identified by each property.

• Restorative Dentistry and Endodontics
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• v.48 no.4
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• pp.41.1-41.17
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• 2023

Objectives: This scientometric and bibliometric analysis explored scientific publications related to hydraulic calcium silicate-based (HCSB) sealers used in endodontology, aiming to describe basic bibliometric indicators and analyze current research trends. Materials and Methods: A comprehensive search was conducted in Web of Science and Scopus using specific HCSB sealer and general endodontic-related terms. Basic research parameters were collected, including publication year, authorship, countries, institutions, journals, level of evidence, study design and topic of interest, title terms, author keywords, citation counts, and density. Results: In total, 498 articles published in 136 journals were retrieved for the period 2008-2023. Brazil was the leading country, and the universities of Bologna in Italy and Sao Paolo in Brazil were represented equally as leading institutions. The most frequently occurring keywords were "calcium silicate," "root canal sealer MTA-Fillapex," and "biocompatibility," while title terms such as "calcium," "sealers," "root," "canal," "silicate based," and "endodontic" occurred most often. According to the thematic map analysis, "solubility" appeared as a basic theme of concentrated research interest, and "single-cone technique" was identified as an emerging, inadequately developed theme. The co-occurrence analysis revealed 4 major clusters centered on sealers' biological and physicochemical properties, obturation techniques, retreatability, and adhesion. Conclusions: This analysis presents bibliographic features and outlines changing trends in HCSB sealer research. The research output is dominated by basic science articles scrutinizing the biological and specific physicochemical properties of commonly used HCSB sealers. Future research needs to be guided by studies with a high level of evidence that utilize innovative, sophisticated technologies.

• Language and Information
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• v.13 no.1
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• pp.93-125
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• 2009

We examine attributive possessive constructions in Korean in examples like wuli manwula 'my wife' and wuli nala 'my country', where an apparently plural pronoun wuli 'our' is used to convey the singular meaning of 'my.' An example like wuli manwula has been a frequent topic of joke, because it clearly contains the literal sense of 'shared wife.' This type of use and the frequent use of wuli in an exclusive my context led many to claim that these are products of Korean culture which emphasizes groups and group solidarity over individuality, the example wuli manwula being the extreme case. Drawing on the work of Taylor (1989; 1996), Croft (2001; 2003), Haspelmath (1997; 2003), and 윤재학 (2003), we compare the meanings of Korean and English possessive constructions and seek a more linguistically based account for the data. In particular, it is shown that (i) wuli in question is not really the plural form of nay 'my', (ii) the possessive constructions in Korean are more conservative and limited in possible relations than the English counterparts are, and that (iii) these two facts interact to produce the afore-mentioned uses.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.107-114
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• 2016

Recently, 3D related technology has become a hot topic for IT. 3D technologies such as 3DTV, Kinect and 3D printers are becoming more and more popular. According to the flow of the times, the goal of this study is that the general public is exposed to 3D technology easily. we have developed a web-based application program that enables 3D modeling of facial front and side photographs using a mobile phone. In order to realize 3D modeling, two photographs (front and side) are photographed with a mobile camera, and ASM (Active Shape Model) and skin binarization technique are used to extract facial height such as nose from facial and side photographs. Three-dimensional coordinates are generated using the face extracted from the front photograph and the face height obtained from the side photograph. Using the 3-D coordinates generated for the standard face model modeled with the standard face as a control point, the face becomes the face of the subject when the RBF (Radial Basis Function) interpolation method is used. Also, in order to cover the face with the modified face model, the control point found in the front photograph is mapped to the texture map coordinate to generate the texture image. Finally, the deformed face model is covered with a texture image, and the 3D modeled image is displayed to the user.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.84-97
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• 2021

Digital twins are one of the promising digital technologies used to facilitate digital transformation. Therefore, it needs to continually be developed remain relevant in industry and academia. Consolidation of research is required to create a common understanding of the topic and to ensure that future research is built upon a solid foundation. Based on a bibliometric review and a thematic analysis of 217 publications on digital twins from the past two decades, this paper creates and analyzes a visual knowledge map and proposes areas for further research. To comprehensively analyze the development trends and research trends of digital twins, we performed statistical analysis of the relevant literature on digital twins within the core collection database of Web of Science. Through our research, we have shown that the current situation, trends, and hotspots of digital twin research were analyzed via CiteSpace. This study demonstrates that research on digital twins is rapidly growing in popularity, that the output of the research depends largely on the core group of authors conducting it, and that digital twins warrant cross-domain and cross-disciplinary research pathways.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.771-789
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• 2019

Text detection has been a popular research topic in the field of computer vision. It is difficult for prevalent text detection algorithms to avoid the dependence on datasets. To overcome this problem, we proposed a novel unsupervised text detection algorithm inspired by bootstrap learning. Firstly, the text candidate in a novel form of superpixel is proposed to improve the text recall rate by image segmentation. Secondly, we propose a unique text sample selection model (TSSM) to extract text samples from the current image and eliminate database dependency. Specifically, to improve the precision of samples, we combine maximally stable extremal regions (MSERs) and the saliency map to generate sample reference maps with a double threshold scheme. Finally, a multiple kernel boosting method is developed to generate a strong text classifier by combining multiple single kernel SVMs based on the samples selected from TSSM. Experimental results on standard datasets demonstrate that our text detection method is robust to complex backgrounds and multilingual text and shows stable performance on different standard datasets.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.355-365
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• 2023

This study examined the relationship between corporate governance and risk disclosure via a systematic literature review and bibliometric visualization analysis. The study aimed to present evidence of risk disclosure intellectual structure, volume, and development knowledge trends. Data was extracted from Scopus and analyzed with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and RTools. In turn, 64 articles were extracted from the Scopus database. The results demonstrated that the number of corporate governance and risk disclosure publications increased significantly from 2015 to 2019 compared to before 2015. RTools revealed the most prominent journals, authors, and interests in the field. The co-occurrences map was constructed based on 208 keywords from 64 articles, where the keywords were required to appear once in the research. Interestingly, the keyword search yielded new concepts relatively unexplored in the risk disclosure field. The 13 clusters were generated, which contained 1987 total links and 1567 direct citations. Based on the scientific analysis discussion, corporate governance and risk disclosure is an interesting topic that has produced many publications. Applying research keywords arguably aided in producing and publishing papers in top journals. Despite the number of publications decreasing due to the COVID-19 pandemic, the pandemic also presented new opportunities for future research.

• Journal of the Korean Society for information Management
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• v.33 no.3
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• pp.63-83
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• 2016

As the usage of information resources produced in various media and forms has been increased, the importance of metadata as a tool of information organization to describe the information resources becomes increasingly crucial. The purposes of this study are to analyze and to demonstrate the intellectual structure in the field of metadata through co-word analysis. The data set was collected from the journals which were registered in the Core collection of Web of Science citation database during the period from January 1, 1998 to July 8, 2016. Among them, the bibliographic data from 727 journals was collected using Topic category search with the query word 'metadata'. From 727 journal articles, 410 journals with author keywords were selected and after data preprocessing, 1,137 author keywords were extracted. Finally, a total of 37 final keywords which had more than 6 frequency were selected for analysis. In order to demonstrate the intellectual structure of metadata field, network analysis was conducted. As a result, 2 domains and 9 clusters were derived, and intellectual relations among keywords from metadata field were visualized, and proposed keywords with high global centrality and local centrality. Six clusters from cluster analysis were shown in the map of multidimensional scaling, and the knowledge structure was proposed based on the correlations among each keywords. The results of this study are expected to help to understand the intellectual structure of metadata field through visualization and to guide directions in new approaches of metadata related studies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.12
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• pp.6143-6150
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• 2012

The current society, namely information society is now moving to a specific topic which is SMART. In this sense, recently a variety of social areas including communications and SOC domains are moving fast to this topic. In Korea, The electric power area has been doing a pioneering job relatively successfully and the water supply area is just now taking the first step. The purpose of this research is to develop a technical Framework for Smart Water Grid Service. Related researches has been studied and the 4 constituting technical element areas were defined first. For each of the four areas, a framework modeling was fulfilled and as a result, a TRM(Technical Road Map) was suggested for each of the area. Finally, an Enterprise TRM covering all of the 4 areas was described. Furthermore, the currently suggested Framework model was compared to a related model and it was found that the integration of the models is desirable to wholly cover from Macro to Micro level applications and services. It is expected that the current approach contribute, more or less, to the smart implementation in the areas of water management.