• Journal of Information Technology Services
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• v.13 no.2
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• pp.133-149
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• 2014

It is unavoidable to provide products that meet customers' needs and wants so that firms may survive under the competition in this globalized market. This paper focuses on how to provide levels for attributes that compse product so that firms may give the best products to customers. In particular, its main issue is how to determine common attributes and the others with their appropriate levels to maximize firms' profits, and how to construct a decision support system to ease decision makers' decisons about optimal common attribute selection using the Semantic Web and SWCL technologies. Parameter data in problems and the relationships in the data are expressed in an ontology data model and a set of constraints by using the Semantic Web and SWCL technologies. They generate a quantitative decision making model through the automatic process in the proposed system, which is fed into the solver using the Logic-based Benders Decomposition method to obtain an optimal solution. The system finally provides the generated solution to the decision makers. This presentation suggests the opportunity of the integration of the proposed system with the broader structured data network and other decision making tools because of the easy data shareness, the standardized data structure and the ease of machine processing in the Semantic Web technology.

• The Journal of Society for e-Business Studies
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• v.8 no.4
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• pp.183-205
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• 2003

There have been various attempts of Knowledge Management System in order to effectively support Knowledge Process and to manage a wide variety of unstructured knowledge. However, Knowledge Management System basically has some significant weakness for searching knowledge, extracting information and maintenance, and some difficulties to integrate such various knowledge resources. Several studies had been conducted to overcome these weaknesses and to improve the method of knowledge management. The purpose of this study is 1) to examine the effectiveness of Semantic Web Technology that has a great attention lately; whether it is useful to overcome the weaknesses, and 2) to review its strong points and some future uses. Further, differences of Semantic Web Technology compared to existing Knowledge Management System Architecture are reviewed. Finally, a new Semantic Web Enabled KMS Architecture is proposed. Also some prospects for future market direction are suggested.

• Journal of Information Management
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• v.41 no.3
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• pp.175-190
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• 2010

In order to enhance national science technology and to secure the origin of creative wealth, there is a need to offer accurate and high quality information with semantic technology. Semantic technology enables to significantly unify information and obtain the wanted information in an easier way. Also Semantic technology is a key technology of the next generation having great ripple effect on the whole of IT. In this paper, We analyze an economic ripple effects in terms of production inducement effect, added value inducement effect, import inducement effect, labor inducement effect of Semantic technology using an input-out analysis of the bank of Korea(2009). We also examine an economic propriety of Semantic technology.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.111-124
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• 2011

The apartment' share of the housing has steadily increased and property assets have been valued in importance as the one of asset value. Information retrieval system using internet is particularly active in the real estate market. However, user satisfaction on real estate information system is not very high, and there is a lack of research on real estate retrieval to increasing efficiency until now. This study presents a new knowledge information system developed to consider region-related factor and individual-related factor in the real estate market. In addition it enables a real estate knowledge system to search various preferential requirements for buyers such as school district, living convenience, easy maintenance as well as price. We made a survey of the search condition preference of experts on 30 real estate agents and then analyzed the result using AHP methodology. Furthermore, this research is to build apartment ontology using semantic web technologies to standardize various terminologies of apartment information and to show how it can be used to help buyers find apartments of the interest. After designing architecture of a real estate knowledge information system, this system is applied to the Busan real estate market to estimate the solutions of retrieval through Multi-Attribute Decision Making(MADM). Based on the results of the analysis, we endowed the buyer and expert's selected factors with weights in the system. Evaluation results indicate that this new system is to raise not only the value satisfaction of user, but also make it possible to effectively search and analyze the real estate through entropy analysis of MADM. This new system is to raise not only the value satisfaction of buyer's real estate, but also make it possible to effectively search and analyze the related real estate, consequently saving the searching cost of the buyers.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.66-71
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• 2021

The purpose of this paper is to identify keywords related to museums, gamification, and visitors, and provide basic data that the museum market can be expanded by using gamification. That used to collect data for blogs, news, cafes, intellectuals, academic information by Naver and Daum which is Web documents in Korea, and Google Web, news, Facebook, Baidu, YouTube, and Twitter for analysis. For the data analysis period, a total of one year of data was selected from April 16, 2020 to April 16, 2021, after Corona. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analysed and visualized using the Netdraw function in the UCINET6 program. In addition, We performed CONCOR analysis to derive clusters for similar keywords. As a result, a total of 25,761 cases that analysing the keywords of museum, gamification and visitors were derived. This shows that the museum, gamification, and spectators are related to each other. Furthermore, if a system using gamification is developed for museums, the museum market can be developed.

• Journal of Information Technology Services
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• v.17 no.2
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• pp.165-177
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• 2018

Recently, online commerces are becoming more common due to factors such as mobile technology development and smart device dissemination, and online review has a big influence on potential buyer's purchase decision. This study presents a set of analytical methodologies for understanding the meaning of customer reviews of products in online transaction. Using techniques currently developed in deep learning are implemented Hierarchical Attention Network for analyze meaning in online reviews. By using these techniques, we could solve time consuming pre-data analysis time problem and multiple topic problems. To this end, this study analyzes customer reviews of laptops sold in domestic online shopping malls. Our result successfully demonstrates over 90% classification accuracy. Therefore, this study classified the unstructured text data in the semantic analysis and confirmed the practical application possibility of the review analysis process.

• The Journal of Information Systems
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• v.18 no.1
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• pp.47-76
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• 2009

The economic growth that depended on IT industry is reaching to a limit. In order to overcome the limit, the convergence industry that makes new market and products is essential. However, companies preparing a jump into the convergence industry must understand the exact visions and characteristics of convergence. Therefore, we investigated the structural changes of industries caused by convergence and importance characteristics of convergence. Also, we demonstrated the current status of the convergence industry and analyzed economical, social/cultural, and technological environments that the companies are facing, and elaborated the opportunities of convergence. At last, we suggested basic requirements and strategies for companies starting a convergence business and IT utilization methods to accelerate the convergence business activation.

• Journal of Technology Innovation
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• v.21 no.1
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• pp.279-301
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• 2013

This study demonstrates how social network analysis can be used for identifying potential buyers in technology marketing; in such, the methodology and empirical results are proposed. First of all, we derived the three most important 'seed' keywords from 'technology description' sections. The technologies are generated by various types of R&D activities organized by South Korea's public research institutes in the fundamental science fields. Second, some 3, 000 words were collected from websites related to the three 'seed' keywords. Next, three network matrices (i.e., one matrix per seed keyword) were constructed. To explore the technology network structure, each network is analyzed by degree centrality and Euclidean distance. The network analysis suggests 100 potentially demanding companies and identifies seven common companies after comparing results derived from each network. The usefulness of the result is verified by investigating the business area of the firm's homepages. Finally, five out of seven firms were proven to have strong relevance to the target technology. In terms of social network analysis, this study expands its application scope of methodology by combining semantic network analysis and the technology marketing method. From a practical perspective, the empirical study suggests the illustrative framework for exploiting prospective demanding companies on the web, raising possibilities of technology commercialization in the basic research fields. Future research is planned to examine how the efficiency of process and accuracy of result is increased.

• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.313-325
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• 2022

The purpose of this study is to examine the changes in the elderly healthcare app market through text mining analysis and to present basic data for activating elderly healthcare apps. Data collection was conducted on Naver, Daum, blog web, and cafe. As for the research method, text mining, TF-IDF(Term frequency-inverse document frequency), emotional analysis, and semantic network analysis were conducted using Textom and Ucinet6, which are big data analysis programs. As a result of this study, a total of six categories were finally derived: resolving the healthcare app information gap, convergence healthcare technology, diffusion media, elderly healthcare app industry, social background, and content. In conclusion, in order for elderly healthcare apps to be accepted and utilized by the elderly, they must have a good diffusion infrastructure, and the effectiveness of healthcare apps must be maximized through the active introduction of convergence technology and content development that can be easily used by the elderly.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.133-142
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• 2004

The next generation of web applications will need to be larger, more complex, and flexible Agent-oriented systems have great potential for these e-commerce applications. Agents can dynamically discover and compose e-services and mediate interactions. Development of software agents with CBD (Component Based Development) has proved to be successful in increasing speed to market of development Projects, lowering the development cost and providing better qualify. In this thesis, we propose a systemic development process for software agents using component and UML (Unified Modeling Language). We suggest a etA (e-business Agent) CBD reference architecture for layer the related components through identification and classification of general agent and e-business agent. We also propose the ebA-CBD process that is a guideline to consider the best features of existing agent oriented software engineering methodologies, while grounding agent-oriented concepts in the same underlying semantic framework used by UML. We first developed the agent components specification and modeled it with Goal, Role, Interaction, and Architecture Model. Based on this, we developed e-CPIMAS (e-Commerce Product Information Mailing Agent System) as a case study that provides the product information's mailing service according to proposed process formality. We finally describe how these concepts may assist in increasing the efficiency reusability, productivity and quality to develop the business application and e-business agent.