• The KIPS Transactions:PartD
• /
• v.13D no.4 s.107
• /
• pp.525-534
• /
• 2006

Ontology specifies the knowledge in a specific domain and defines the concepts of knowledge and the relationships between concepts. It is possible to provide the service based on the semantic web through the ontology. Therefore, to specify and define the knowledge in a specific domain, it is required to generate the ontology which conceptualizes the knowledge. Accordingly, to search the information of potential customers for home-delivery marketing of post office, we design the specific domain to generate the ontology based on the semantic web in this paper. And we propose how to retrieve the information, using the generated ontology. We implement the data search robot which collects the information based on the generated ontology. Also, we confirm that the ontology and the search robot perform the information retrieval exactly.

• CELLMED
• /
• v.13 no.2
• /
• pp.3.1-3.21
• /
• 2023

In this study, the drinking culture of the Choseon dynasty is examined with the text frequency analysis technique on the entire 『Choseonwangjosilok (朝鮮王朝實錄)』. This study examined a total of 1,968 volumes and 948 books about 27 kings of Choseon , which spans a total of 518 years, through web crawling on the National Institute of Korean History website. Python 3.8 was used to extract sentences related to alcohol, Rhino 1.4.5 was used for morphological analysis to extract nouns, and Gephi 0.9.2 was used for semantic network analysis. According to 『Choseonwangjosilok (朝鮮王朝實錄)』 about alcohol culture, the results of the analysis are as follow: Alcoholic beverages were more often used in court or in ritual ceremonies rather than those based on specific ingredients or manufacturing methods commonly used by the general public. regarding the ruling class through semantic network analysis l in the 『Choseonwangjosilok (朝鮮王朝實錄)』, the Choseon dynasty was found to be highly associated with political issues related to maintaining the power relations within the Korean royal court system. At times, alcohol was used to maintain personal relationships, while at other times it was seen as an essential item in state ceremonies. It was also used as a highly political means to maintain and strengthen national power.

• Journal of Internet Computing and Services
• /
• v.13 no.1
• /
• pp.107-115
• /
• 2012

In recent Information Environment, various Multimedia contents are getting noticed. But, since these contents have various formats of representation and very wide range of information, it was difficult to retrieve contents that user wanted and to utilize it. To solve these problems, many studies presented draft standards for adding metadata to contents, and then, semantic search for contents had become available. Unfortunately, as the number of metadata standards and contents increased, the lack of interoperability between contents was begun and users are faced with difficulty of search contents again. To improve these problems, this paper supports interoperability between metadata standards and expands the semantic relationship between elements and proposes an ontology which is named TOFIC(The Ontology For Imagery Contents) for enhanced semantic search. In TOFIC, the semantic relationships between MPEG-7 and TV-Anytime are classified, and extended new semantics are defined. As a result, semantic search for multimedia contents is enhanced and it is possible to retrieve most of the multimedia contents that exist on the current information environment consistently. In addition, it supports enhanced content-based search for multimedia contents.

• Journal of Information Management
• /
• v.39 no.4
• /
• pp.121-154
• /
• 2008

In this paper, a ontology-based keyword structuring method is proposed to represent the knowledge structure of scholarly documents and to make inferences from the semantic relationships holding among them. The characteristics of thesaurus as a knowledge organization system(KOS) for subject heading is critically reviewed from the information retrieval point of view. The domain concepts are identified and classified by analysis of the information activities occurring in a general research process based on scholarly sensemaking model. The ontological structure of keyword set is defined in terms of the semantic relationship of the canonical concepts which constitute scholarly documents such as journal articles. As a result, each ontologically structured keyword set of a document represents the knowledge structure of the corresponding document as semantic index. By means of the axioms and inference rules defined for information needs, users can efficiently explore the scholarly communication network built on the semantic relationship among documents in an analytic way based on the scholarly sensemaking model in oder to efficiently retrieve the relevant information for problem solving.

• The KIPS Transactions:PartA
• /
• v.14A no.4
• /
• pp.209-214
• /
• 2007

In conventional game systems, virtual environments usually have just the role of a background without the direct relationships for game characters. nev do not consider the semantics about virtual environments. In this paper, we develop a game navigation system that provides semantic information about virtual environments including geographical, historical or my other location-dependent information. Then, the game character obtains the geographical location and its related information when it navigates through a virtual environment. It can be an implementation method for a semantic virtual environment because it can have the environment maintain its semantics depending on the specific location. In addition, we describe a method that can control a character's motion in the semantic virtual environment interactively, and that can input specific information according to the location of the character.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.10
• /
• pp.2643-2657
• /
• 2023

Scene graphs are structured representations that can clearly convey objects and the relationships between them, but are often heavily biased due to the highly skewed, long-tailed relational labeling in the dataset. Indeed, the visual world itself and its descriptions are biased. Therefore, Unbiased Scene Graph Generation (USGG) prefers to train models to eliminate long-tail effects as much as possible, rather than altering the dataset directly. To this end, we propose Geometric and Semantic Improvement (GSI) for USGG to mitigate this issue. First, to fully exploit the feature information in the images, geometric dimension and semantic dimension enhancement modules are designed. The geometric module is designed from the perspective that the position information between neighboring object pairs will affect each other, which can improve the recall rate of the overall relationship in the dataset. The semantic module further processes the embedded word vector, which can enhance the acquisition of semantic information. Then, to improve the recall rate of the tail data, the Class Balanced Seesaw Loss (CBSLoss) is designed for the tail data. The recall rate of the prediction is improved by penalizing the body or tail relations that are judged incorrectly in the dataset. The experimental findings demonstrate that the GSI method performs better than mainstream models in terms of the mean Recall@K (mR@K) metric in three tasks. The long-tailed imbalance in the Visual Genome 150 (VG150) dataset is addressed better using the GSI method than by most of the existing methods.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.12 no.3
• /
• pp.311-325
• /
• 2016

This study aims to investigate strategies for attracting consumers in Urban Entertainment Centers and understand the relationship between user satisfaction and intention of revisiting. To accomplish this, the strategic attraction factors were set as functional, experiential, episodic, and semantic. The relationships between these factors and revisiting intentions were studied experimentally. The result of the study can be summarized to 3 points. First, the 4 strategic factors that were selected all had a significant influence on revisiting intention. Therefore the more these factors have an influence, the higher the satisfaction and revisiting intentions. Secondly, out of the attraction factors the one with the biggest influence to customer satisfaction turned out to be 'functional factors' which is related to convenience, accessibility and availability. The factor that had the biggest influence on revisiting intentions turned out to be 'semantic factors' which is related to events, unusualness and temporality. Through this result we can see that to enhance satisfaction 'functional factors' should be considered first and to increase revisiting intentions 'episodic factors' should be considered first. Thirdly, it could be assumed that satisfaction of the visitors could boost intentions of revisiting.

• Journal of Korea Society of Industrial Information Systems
• /
• v.12 no.4
• /
• pp.25-31
• /
• 2007

An automatic term-network construction system is proposed in this paper. This system uses the statistical values of the terms appeared in a document corpus. The 186 oral history documents collected from the Saemangeum area of Chollapuk-do, Korea, are used for the research. The term relationships presented in the term-network are decided by the cosine similarities of the term vectors. The number of the terms extracted from the documents is about 1700. The system is able to show the term relationships from the term-network as quickly as like a real-time system. The way of this term-network construction is expected as one of the methods to construct the ontology system and to support the semantic retrieval system in the near future.

• The Journal of Information Systems
• /
• v.30 no.2
• /
• pp.189-214
• /
• 2021

Purpose This paper aims to effectively utilize user-generated content (UGC) and analyze the market structure of a relatively new market which lacks rich user review information. Specifically, we propose a domain-specific text mining tool for the domestic craft beer market and visualize the market structure by incorporating how individual beer products are positioned in the perceptual map of consumers. Design/methodology/approach We collect user review information from Naver blogs, and extract words that describe beers. We identify semantic relationships between beer products through text mining, and then depending on these semantic relationships, construct a graph representing the market structure of the domestic craft beer market based on the consumer's perceptual map. Findings First, beer products produced in the same brewery are perceived as very similar to consumers. Second, only two products, 'Heukdang Milky Stout' and 'Gompyo', was noticeably distinguishable from other products. Third, even though 'Gyeongbokgung' is from a different brewery, it is located very close to the products of 'Jeju Beer' brewery such as 'Jeju Baeknokdam Ale' and 'Seongsan Ilchulbong Ale', which suggests the influence of 'landmark series.' We successfully show that our methodology effectively describes the market structure of the craft beer market.

• Journal of the Korean Society for information Management
• /
• v.23 no.1 s.59
• /
• pp.63-81
• /
• 2006

The purpose of this study is to present the limitation of terminological relationships in the current information environment and to propose a solution to result in the richer and refined terminological resources. For this, various kinds of terminological relationships in knowledge organization systems and theoretical researches were collected and analyzed. Based upon the analysis, a methodology for classification of terminological relationships was suggested and classification models were presented. Additionally, four suggestions were made for the practical uses of the classification models.