• Journal of Digital Convergence
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• v.14 no.11
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• pp.267-273
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• 2016

Creation and Sharing of information which is structured data as well as various unstructured data. makes progress actively through the spread of mobile. Recently, Big Data extracts the semantic information from SNS and data mining is one of the big data technique. Especially, the general emotion analysis that expresses the collective intelligence of the masses is utilized using large and a variety of materials. In this paper, we propose the emotion prediction system architecture which extracts the significant keywords from social network paragraphs using n-gram and Korean morphological analyzer, and predicts the emotion using SVM and these extracted emotion features. The proposed system showed 82.25% more improved recall rate in average than previous systems and it will help extract the semantic keyword using morphological analysis.

• The Journal of the Korea Contents Association
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• v.6 no.11
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• pp.249-259
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• 2006

E-learning objects should be appropriately described and classified using standard metadata for facilitating the processes of e-learning resource description, discovery and reuse. These metadata need to be published in a registry to reduce duplication of effort and enhance semantic interoperability. This paper describes how standard ebXML registries can be used for annotating, storing, discovering and retrieving e-learning object metadata. For semantic annotation of e-learning objects, IEEE LOM is adopted as the metadata ontology. In order to support the e-learning metadata ontology in interoperable ebXML registries, a mapping scheme between LOM and ebXML information model is proposed. The usefulness of standard ebXML registries for sharing e-learning metadata is demonstrated by prototyping an e-learning registry called ebRR4LOM based on the scheme.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.1-10
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• 2021

This paper aimed to look at the awareness of foreign workers in social platforms by using text mining, one of the big data techniques and draw suggestions for foreign workers. To achieve this purpose, data collection was conducted with search keyword 'Foreign Worker' from Jan. 1, to Dec. 31, 2020, and frequency analysis, TF-IDF analysis, and degree centrality analysis and 100 parent keywords were drawn for comparison. Furthermore, Ucinet6.0 and Netdraw were used to analyze semantic networks, and through CONCOR analysis, data were clustered into the following eight groups: foreigner policy issue, regional community issue, business owner's perspective issue, employment issue, working environment issue, legal issue, immigration issue, and human rights issue. Based on such analyzed results, it identified national awareness of foreign workers and main issues and provided the basic data on policy proposals for foreign workers and related researches.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.105-115
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• 2022

This study compares the perspectives of experts and the public on the 2015 revised curriculum. To do this, research papers and newspaper articles were collected from October 2013 to May 2020. During this period, 1152 research papers and 692 newspaper articles were collected, and semantic network analysis was performed. As a result of the study, the educational expert group showed great interest in the core concept of the development of the revised curriculum focused on the abstract concept, while the public focused on the practical problems and consequences of the revision rather than the development of the revised curriculum itself. These results not only show the gap between the perspectives of the educational expert group and the public but also raise the need for effective communication to bridge the gap.

• Journal of Nutrition and Health
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• v.56 no.3
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• pp.330-347
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• 2023

Purpose: This study identified words closely associated with the keyword "dietary supplement" (DS) using big data in Korean social media and investigated consumer perceptions and trends related to DSs before (2019) and after the coronavirus disease 2019 (COVID-19) pandemic (2021). Methods: A total of 37,313 keywords were found for the 2019 period, and 35,336 keywords were found for the 2021 period using blogs and cafes on Daum and Naver. Results were derived by text mining, semantic networking, network visualization analysis, and sentiment analysis. Results: The DS-related keywords that frequently appeared before and after COVID-19 were "recommend", "vitamin", "health", "children", "multiple", and "lactobacillus". "Calcium", "lutein", "skin", and "immunity" also had high frequency-inverse document frequency (TF-IDF) values. These keywords imply a keen interest in DSs among Korean consumers. Big data results also reflected social phenomena related to DSs; for example, "baby" and "pregnant woman" had lower TD-IDF values after the pandemic, suggesting lower marriage and birth rates but higher values for "joint", indicating reduced physical activity. A network centered on vitamins and health care was produced by semantic network analysis in 2019. In 2021, values were highest for deficiency and need, indicating that individuals were searching for DSs after the COVID-19 pandemic due to a lack an awareness of the need for adequate nutrient intake. Before the pandemic, DSs and vitamins were associated with healthcare and life cycle-related topics, such as pregnancy, but after the COVID-19 pandemic, consumer interests changed to disease prevention and treatment. Conclusion: This study provides meaningful clues regarding consumer perceptions and trends related to DSs before and after the COVID-19 pandemic and fundamental data on the effect of the pandemic on consumer interest in dietary supplements.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.60-68
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• 2024

Purpose: When designing plants and workplaces such as handling and using chemicals, a system that can automatically determine whether the design has been made in compliance with domestic safety management laws is established to shorten the review time and increase accuracy. Method: Safety design standards for chemical handling and use workplaces were investigated, and types and systems were derived that could automatically judge design errors by dividing the articles into semantic units. Result: An automatic design review method performed when designing a building was proposed, and a system that can review the safety design requirements required when designing a chemical handling business site through the development of a rule checker was proposed. After confirming whether the law is subject to application, the safety design rules are classified into semantic units through preprocessing. The classified results can be classified into four types, and the specifications, space, conditions, situations, and specific devices and facilities to reinforce safety were analyzed as representative types. It proposes a system that prepares a diagram for the safety design rule and allows it to be reviewed through the rule checker program.

• Journal of Contemporary Eastern Asia
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• v.23 no.1
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• pp.18-34
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• 2024

In what was labeled the "nut rage" incident, the vice president of Korean Air, Hyun-Ah Cho (Heather Cho), demonstrated behavior that exemplifies corporate transgression and deviation from societal moral standards toward a flight attendant aboard a flight. Such behavior instigated the public to express negative sentiment on various social media platforms. This study investigates word-of-mouth network on YouTube in response to the crisis, patterns of co-commenting activities across selected YouTube videos, as well as public responses to the incident by employing social and semantic network analysis. A total of 512 YouTube videos featuring the crisis from December 8, 2014 through November 11, 2018, and 52,772 public comments to the videos were collected. The central videos in the network successfully attracted the public's attention and engagements. The results suggest that the video network was decentralized, with multiple videos acting as hubs in the network. The public commented on various videos instead of focusing on a few. The contents of influential videos uploaded by popular news organizations revealed not only Cho's behaviors related to the nut rage crisis but also unrelated illegal behaviors and the moral violations committed by the family members of Korean Air. The public attached derogatory remarks to Cho and her family, and the comments also addressed ethical concerns, management issues of the company, and boycott intentions. The results imply that adverse public reaction was related to the long-standing problem caused by family ownership and governance in large Korean corporations. This Korean Air scandal illustrates backlash toward a leadership breakdown by the family business conglomerate prevalent in the Korean society. This study provides insights for effective handling of similar crises.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.102-116
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• 2006

Electronic catalogs (or e-catalogs) hold information about the goods and services offered or requested by the participants, and consequently, form the basis of an e-commerce transaction. Catalog management is complicated by a number of factors and product classification is at the core of these issues. Classification hierarchy is used for spend analysis, custom3 regulation, and product identification. Classification is the foundation on which product databases are designed, and plays a central role in almost all aspects of management and use of product information. However, product classification has received little formal treatment in terms of underlying model, operations, and semantics. We believe that the lack of a logical model for classification Introduces a number of problems not only for the classification itself but also for the product database in general. It needs to meet diverse user views to support efficient and convenient use of product information. It needs to be changed and evolved very often without breaking consistency in the cases of introduction of new products, extinction of existing products, class reorganization, and class specialization. It also needs to be merged and mapped with other classification schemes without information loss when B2B transactions occur. For these requirements, a classification scheme should be so dynamic that it takes in them within right time and cost. The existing classification schemes widely used today such as UNSPSC and eClass, however, have a lot of limitations to meet these requirements for dynamic features of classification. In this paper, we try to understand what it means to classify products and present how best to represent classification schemes so as to capture the semantics behind the classifications and facilitate mappings between them. Product information implies a plenty of semantics such as class attributes like material, time, place, etc., and integrity constraints. In this paper, we analyze the dynamic features of product databases and the limitation of existing code based classification schemes. And describe the semantic classification model, which satisfies the requirements for dynamic features oi product databases. It provides a means to explicitly and formally express more semantics for product classes and organizes class relationships into a graph. We believe the model proposed in this paper satisfies the requirements and challenges that have been raised by previous works.

• The KIPS Transactions:PartD
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• v.12D no.1 s.97
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• pp.165-178
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• 2005

A product classification scheme is the foundation on which product databases are designed, and plays a central role in almost all aspects of management and use of product information. It needs to meet diverse user views to support efficient and convenient use of product information. It needs to be changed and evolved very often without breaking consistency in the cases of introduction of new products, extinction of existing products, class reorganization, and class specialization. It also needs to be merged and mapped with other classification schemes without information loss when B2B transactions occur. For these requirements, a classification scheme should be so dynamic that it takes in them within right time and cost. The existing classification schemes widely used today such as UNSPSC and eCl@ss, however, have a lot of limitations to meet these requirements for dynamic features of classification. Product information implies a plenty of semantics such as class attributes like material, time, place, etc., and integrity constraints. In this Paper, we analyze the dynamic features of product databases and the limitation of existing code based classification schemes, and describe the semantic classification model proposed in [1], which satisfies the requirements for dynamic features of product databases. It provides a means to explicitly and formally express more semantics for product classes and organizes class relationships into a graph.

• Journal of Information Management
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• v.37 no.2
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• pp.1-20
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• 2006

It has lately been recognized that the sharing and exchanging of the research results information is the critical factor to improve the research productivity. So many institutions are planning or developing the information systems which provide the research information services for researcher. But it has very difficulty in integrating the research resources information due to the dispersion and heterogeneity in data sources, and semantic and structural difference in describing data. We propose the semantic web based methodology and conceptual framework for raising the interoperability of metadata about research results information, which will support the integration of the distributed research data for information services in the end. We first introduce the ontology which is developed based on Standard Metadata of Research Results Information published by STISC. Then to show the applicability in real-world environment, we express the metadata of research information in RDF/RDFS according to ontology. Finally we proposed the conceptual architecture of research information service system which shows the main components, the functional requirements, and the principal and design direction at implementing the system.