• Culinary science and hospitality research
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• v.23 no.4
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• pp.22-32
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• 2017

The purpose of this study was to explore awareness of food tourism using big data analysis. For this, this study collected data containing 'food tourism' keywords from google web search, google news, and google scholar during one year from January 1 to December 31, 2016. Data were collected by using SCTM (Smart Crawling & Text Mining), a data collecting and processing program. From those data, degree centrality and eigenvector centrality were analyzed by utilizing packaged NetDraw along with UCINET 6. The result showed that the web visibility of 'core service' and 'social marketing' was high. In addition, the web visibility was also high for destination, such as rural, place, ireland and heritage; 'socioeconomic circumstance' related words, such as economy, region, public, policy, and industry. Convergence of iterated correlations showed 4 clustered named 'core service', 'social marketing', 'destinations' and 'social environment'. It is expected that this diagnosis on food tourism according to changes in international business environment by using these web information will be a foundation of baseline data useful for establishing food tourism marketing strategies.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.101-108
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• 2017

A wireless image sensor node collecting image data for environmental monitoring or surveillance requires a large amount of energy to transmit the huge amount of video data. Even though solar energy can be used to overcome the energy constraint, since the collected energy is also limited, an efficient energy management scheme for transmitting a large amount of video data is needed. In this paper, we propose a method to reduce the number of blackout nodes and increase the amount of gathered data by selecting an appropriate video coding method according to the energy condition of the node in a solar-powered wireless video sensor network. This scheme allocates the amount of energy that can be used over time in order to seamlessly collect data regardless of night or day, and selects a high compression coding method when the allocated energy is large and a low compression coding when the quota is low. Thereby, it reduces the blackout of the relay node and increases the amount of data obtained at the sink node by allowing the data to be transmitted continuously. Also, if the energy is lower than operating normaly, the frame rate is adjusted to prevent the energy exhaustion of nodes. Simulation results show that the proposed scheme suppresses the energy exhaustion of the relay node and collects more data than other schemes.

• Journal of Environmental Health Sciences
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• v.43 no.5
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• pp.412-421
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• 2017

Objectives: To establish a system for integrated risk assessment of EDCs in Korea, infrastructure for providing toxicity data of ecological media should be established. Some systems provide soil ecotoxicity databases along with aquatic ecotoxicity information, but a well-structured ecotoxicity database system is still lacking. Methods: Aquatic and soil ecotoxicological information were collected by a toxicologist based on a human readable data (HRD) format for collecting ecotoxicity data that we provided. Among these data, anomalies were removed according to database normalization theory. Also, the data were cleaned and encoded to establish a machine-readable data (MRD) ecotoxicity database system. Results: We have developed a multi-purpose ecotoxicity database model focusing on EDCs, ecological species, and toxic effects. Also, we have constructed a web-based data searching system to retrieve, extract, and download data with greater availability. Conclusions: The results of our study will contribute to decision-making as a tool for efficient ecological risk assessment of EDCs in Korea.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.144-152
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• 2018

This study focuses on collecting traffic data using drones to compensate for limitation of the data collected by the existing traffic data collection devices. Feasibility analysis was performed to verify the traffic data extracted from drone videos and optimal methodology for extracting data was established through analysis of various data reduction scenarios. It was found from this study that drones are very economical traffic data collection devices and have strength of determining the level-of-service(LOS) for uninterrupted flow condition in a very simple and intuitive way.

• The Journal of Economics, Marketing and Management
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• v.10 no.3
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• pp.21-36
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• 2022

Purpose: The purpose of this study is to compare and analyze the enterprise's score index calculated from atypical data and corrected data. Research design, data, and methodology: In this study, news articles which are non-financial information but qualitative data were collected from 2,432 SMEs that has been extracted "square proportional stratification" out of 18,910 enterprises with fixed data and compared/analyzed each enterprise's score index through text mining analysis methodology. Result: The analysis showed that qualitative data can be quantitatively evaluated by region, industry and period by collecting news from SMEs, and that there are concerns that it could be an element of alternative credit evaluation. Conclusion: News data cannot be collected even if one of the small businesses is self-employed or small businesses has little or no news coverage. Data normalization or standardization should be considered to overcome the difference in scores due to the amount of reference. Furthermore, since keyword sentiment analysis may have different results depending on the researcher's point of view, it is also necessary to consider deep learning sentiment analysis, which is conducted by sentence.

• Journal of Broadcast Engineering
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• v.28 no.3
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• pp.275-284
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• 2023

Gene expression data can be utilized in various studies, including the prediction of disease prognosis. However, there are challenges associated with collecting enough data due to cost constraints. In this paper, we propose a gene expression data generation model based on Conditional Variational Autoencoder. Our results demonstrate that the proposed model generates synthetic data with superior quality compared to two other state-of-the-art models for gene expression data generation, namely the Wasserstein Generative Adversarial Network with Gradient Penalty based model and the structured data generation models CTGAN and TVAE.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.112-117
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• 2023

This study aims to find out what tourists' interests and perceptions are like through online big data. Big data for a total of five years from 2018 to 2022 were collected using the Textom program. Sentiment analysis was performed with the collected data. Sentiment analysis expresses the necessity and emotions of city tours in online reviews written by tourists using city tours. The purpose of this study is to extract and analyze keywords representing satisfaction. The sentiment analysis program provided by the big data analysis platform "TEXTOM" was used to study positives and negatives based on sentiment analysis of tourists' online reviews. Sentiment analysis was conducted by collecting reviews related to the city tour. The degree of positive and negative emotions for the city tour was investigated and what emotional words were analyzed for each item. As a result of big data sentiment analysis to examine the emotions and sentiments of tourists about the city tour, 93.8% positive and 6.2% negative, indicating that more than half of the tourists are positively aware. This paper collects tourists' opinions based on the analyzed sentiment analysis, understands the quality characteristics of city tours based on the analysis using the collected data, and sentiment analysis provides important information to the city tour platform for each region.

• Journal of Korean Society for Quality Management
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• v.52 no.2
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• pp.323-340
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• 2024

Purpose: The purpose of this study was to propose useful suggestions by analyzing research Xiaomi which are big data analyses, by collecting data based on Customer Perception in Textom. Methods: The collected data through scraping social media on the Textom site. And data preprocessing was performed using deleting and organizing data(text) that are duplicated, irrelevant, and where there is no meaning. The derived data were analyzed using Textom and Ucinet 6.0 with Text Analysis, WordClould, TF-IDF, Network Analysis, and Emotional analysis. Results: The results of this study are as follows; although the results of Xiaomi's text at domestic and global were similar, it was analyzed that there were perceptions of Xiaomi-related smart home products and cost-effectiveness in Korea, while in foreign countries, there were perceptions of functions and performance centered on smartphones. At domestic and global, the perception of Xiaomi was analyzed to be positive, and implications were presented based on these analysis results. Conclusion: Based on the results, if the product's performance or product competitiveness is considered to be meaningful in the market, and it is expected that there will be an opportunity to change the overall image of Chinese products.

• Korean Security Journal
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• no.35
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• pp.7-36
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• 2013

Collecting international terrorism database is a challenging task not only for criminal justice personnel but also for criminologists in comparison to the case of common types of crime database. Yet, there has been growing interests and efforts in establishing a comprehensive terrorist events data base in the world. This current study has a goal to introduce an example world terrorism database case developed by START center in the United States. The START center developed the Global Terrorism Database (GTD) on the basis of by the Pinkerton Global Intelligence Service data (PGIS) originally collected by the Pinkerton. Furthermore, The START expended the GTD by collecting data from open source terrorist event data via internet and other resources. In this study, specifically, it describes the development and the nature of the GTD in general and the data collection efforts made by the STATA until today. Finally, this study provides a sketchy of the nature of the GTD data by showing the descriptive statistical analyses and time-series analyses result illustrating distribution of the world terrorism events. The limitation, policy implications and contribution of this study discussed in this paper.

• Korean Journal of Legislative Studies
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• v.26 no.3
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• pp.125-159
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• 2020

Amid global pandemic of covid-19, Korean government's response has drawn wide attention among social scientists as well as medical studies. The role of Korean state and civil society has attracted particular attention among others. Yet, this paper criticizes extant studies on Korean case which focus on the extensive intervention of the strong state and subjective attitude of Korean citizens in coping with covid-19. The concept of the strong state lacks social scientific specification and subjective citizens do not match with Korean realities. This article argues that Korean state's capacity in collecting and mobilizing digital data may offer better understanding for the successful responses to the pandemic. First, Korean state is the ultimate coordinator in collecting, analyzing and applying big data about the expansion of covid-19 with its huge network of dataveillance. Also, such role has been largely based upon relevant legal framework and well prepared manuals and cooperation with civic actors and companies. In other words, Korean digital dataveillance had demonstrated its transparency and cooperative governance. Second, such dataveillance capacity has deep roots in the long-term development of Korean state's big data management. Korean state has evolved about thirty years while enhancing digital data network within governments, companies and private sectors. Third, the relationship between Korean state's dataveillance and civil society can be characterized as a state centered push model. This model demonstrates highly effective governmental responses to covid-19 crisis but fall short of building social consensus in balancing individual freedom, human rights and effective containment policies. It means communitarian solidarity among citizens has not been a major factor in Korea's successful response yet.