• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.429-450
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• 2023

The purpose of this study is to examine recent trends and intellectual structures in research related to open data. To achieve this, the study conducted a search for the keyword "open data" in Scopus and collected a total of 6,543 papers from 1999 to 2023. After data preprocessing, the study focused on the author keywords of 5,589 papers to perform network analysis and derive centrality in the field of open data research and linked open data research. As a result, the study found that "big data" exhibited the highest centrality in research related to open data. The research in this area mainly focuses on the utilization of open data as a concept of public data, studies on the application of open data in analysis related to big data as an associated concept, and research on topics related to the use of open data, such as the reproduction, utilization, and access of open data. In linked open data research, both triadic centrality and closeness centrality showed that "the semantic web" had the highest centrality. Moreover, it was observed that research emphasizing data linkage and relationship formation, rather than public data policies, was more prevalent in this field.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• 기호학연구
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• no.57
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• pp.59-90
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• 2018

This paper examines the discussions related to image and signification through the theories of Roland Barthes. We have already been able to see through the studies of Semiotics and Anne H?nault that the denotation is distinguished from the connotation in the linguistic dimension. Through the analysis of the advertising image of Barthes, we have seen that the syntagmatic relationship can make the sense of the image objective. From this study, we also emphasized that it is possible to subjectively interpret images that deviate from the syntagmatic relationship. In addition, we examined the concepts of Studium and Punctum by Barthes. With this we have found that the definition of a personal meaning to objects has a theoretically clear position. Finally, we have been able to understand the concept of 'le sens obtus' through the article ${\ll}$ Le troisi?me sens ${\gg}$. The notion of 'sens obtus' makes it possible to realize that the objective and clear sense of object is not the one chosen primarily from the subject. By facing an object such as an image to be interpreted, the subject is placed in a situation where he is not compelled to choose a meaning but rather he chooses one of the possible senses. This makes it clear that the semantic levels provided by semiotic theories are limited to the analytic dimension.

• Journal of Practical Agriculture & Fisheries Research
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• v.23 no.1
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• pp.89-104
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• 2021

Based on the TF-IDF weighted value that evaluates the importance of words that play a key role, the semantic network analysis(SNA) was conducted on the self-introduction letter of freshman at Korea National College of Agriculture and Fisheries(KNCAF) in 2020. The top three words calculated by TF-IDF weights were agriculture, mathematics, study (Q. 1), clubs, plants, friends (Q. 2), friends, clubs, opinions, (Q. 3), mushrooms, insects, and fathers (Q. 4). In the relationship between words, the words with high betweenness centrality are reason, high school, attending (Q. 1), garbage, high school, school (Q. 2), importance, misunderstanding, completion (Q.3), processing, feed, and farmhouse (Q. 4). The words with high degree centrality are high school, inquiry, grades (Q. 1), garbage, cleanup, class time (Q. 2), opinion, meetings, volunteer activities (Q.3), processing, space, and practice (Q. 4). The combination of words with high frequency of simultaneous appearances, that is, high correlation, appeared as 'certification - acquisition', 'problem - solution', 'science - life', and 'misunderstanding - concession'. In cluster analysis, the number of clusters obtained by the height of cluster dendrogram was 2(Q.1), 4(Q.2, 4) and 5(Q. 3). At this time, the cohesion in Cluster was high and the heterogeneity between Clusters was clearly shown.

• The Journal of the Korea Contents Association
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• v.8 no.10
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• pp.151-157
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• 2008

This study aims to construct the aged portal sites based on multimedia DB on the basis of request for systematic collection and management of the aged-related specific information which are spreading and construct Multimedia Information System for the Aged by developing digital contents to offer the aged-related information. It also tries to construct ontology based information repository for the aged that includes on/off-line. It extracts semantic relationship of each information by analysing the aged information, knows the hierarchical structure of each vocabulary, and designs and constructs an ontology based repository by designing function of each agent through that. It has also developed a variety of information and digital contents, constructed a systematic multimedia DB for the aged welfare homes, developed web framework which makes automatic registration of the aged welfare homes possible, and designed in order to support the use state of enterprises/homes and statistics state.

• Journal of the Korean Society of Clothing and Textiles
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• v.36 no.10
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• pp.1028-1039
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• 2012

This study identified color emotion factors of naturally dyed two-color combination fabrics focused on yellowish and reddish shades to examine the relationship between color emotion factors and physical colorimetric variables (as well as tone combination groups) to provide prediction models for color emotion factors of naturally dyed fabrics with a two-color combination. Each of eight different stimuli were prepared by paring two pieces of silk fabrics colored in red and yellow by natural dyeing respectively; in addition, their color emotion descriptors were evaluated by human subjects using semantic deferential scales. 'Joyful', 'Natural', 'Classical', and 'Soft' were extracted as color emotion factors for the naturally dyed yellowish-reddish combination fabrics. They were found to be significantly affected by physical colorimetric variables such as CIE $C^*$ and $L^*$ and tone combination groups. Finally, prediction models for all color emotion factors were established using physical colorimetric variables and tone combination groups that led to the conclusion that they could be applicable to design a color combination for naturally dyed fashion fabrics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1637-1646
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• 2009

Recently many researchers have been studying various methods for data integration. Among the integration methods that the researchers have studied, there are a method using metadata repository, and Topic Map which identifies the relationships between the data. This study suggests Meta-Topic Map to create Topic Map about search keyword by applying metadata and Topic Map, and the XMDR as a way to connect Meta-Topic Map with metadata in the legacy system. Considering the semantic relationship of user's keyword in the legacy system, the Meta-Topic Map provides the Topic Map format and generates the Topic Map about user's keyword. The XMDR performs structural integration through solving the problem of heterogeneity among metadata in the legacy system. The suggested svides isproves the interoperability among existing Relational Database constructed in the legacy system and the search efficiency and is efficient in expanding the system.

• Journal of KIISE:Software and Applications
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• v.31 no.11
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• pp.1455-1473
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• 2004

This paper suggests a technique, TELOR(Technique of Object Extraction Based on Legacy System Interface for Improvement of Object Reusability) for reuse and reengineering by analyzing the Legacy System interface to distill the meaningful information from them and disassemble them into object units which are to be integrated into the next generation systems. The TELOR method consists of a 4 steps procedure: 1) the interface use case analysis step, 2) the interface object dividing step, 3) the object structure modeling step, and 4) the object model integration step. In step 1, the interface structure and information about the interaction between the user and the Legacy System are obtained. In step 2, the interface information is divided into semantic fields. In step 3, studies and models the structural and collaborative relationship among interface objects. Finally, in step 4, object model integration step, integrates the models and improves the integrated model at a higher level. The objects integration model created through TELOR provides a more efficient understanding of the Legacy System and how to apply it to next generation systems.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.2
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• pp.131-156
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• 1998

Cooperative query answering is a research effort to develop a fault-tolerant and intelligent database system using the semantic knowledge base constructed from the underlying database. Such knowledge base has two aspects of usage. One is supporting the cooperative query answering Process for providing both an exact answer and neighborhood information relevant to a query. The other is supporting ongoing maintenance of the knowledge base for accommodating the changes in the knowledge content and database usage purpose. Existing studies have mostly focused on the cooperative query answering process but paid little attention on the dynamic knowledge base maintenance. This paper proposes a multi-level knowledge representation framework called Knowledge Abstraction Hierarchy (KAH) that can not only support cooperative query answering but also permit dynamic knowledge maintenance. The KAH consists of two types of knowledge abstraction hierarchies. The value abstraction hierarchy is constructed by abstract values that are hierarchically derived from specific data values in the underlying database on the basis of generalization and specialization relationships. The domain abstraction hierarchy is built on the various domains of the data values and incorporates the classification relationship between super-domains and sub-domains. On the basis of the KAH, a knowledge abstraction database is constructed on the relational data model and accommodates diverse knowledge maintenance needs and flexibly facilitates cooperative query answering. In terms of the knowledge maintenance, database operations are discussed for the cases where either the internal contents for a given KAH change or the structures of the KAH itself change. In terms of cooperative query answering, database operations are discussed for both the generalization and specialization Processes, and the conceptual query handling. A prototype system has been implemented at KAIST that demonstrates the usefulness of KAH in ordinary database application systems.

• Archives of design research
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• v.11 no.3
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• pp.35-44
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• 1998

Acording to the trend of highly increasing the public telephone, understanding consumer's design sensibility is based on designing consumer products reflecting user's identity and it comes out as a result of wore competitive products. For this study, consumer's desirous sensibility of the public telephone has been measured in checkable numbers. First of all, 35 sensible words are narrowed down from 168 whole sensible(adjective) words using the SD method. By this result, 7 scale form the SD method is applied to reserch on 10 current distributed products form 30 male and female university students. Element factor analysis is used to group the selected sensible words, duster analysis is used yo dassify them, and finally discriminant analysis is used to predict the relationship between design elements and the sensible words. As a result, words of human sensibility is known to divide into 3 factors; esthetics, functionality and safety, and the correlation of design factor is closely related with the the telephone's body, handset, dial board, dial button, ontrol button, color and material. To sum up, better public telephone design comes out from scientific and systematic consumer's desire analysis not designer's design technique.