• Journal of Intelligence and Information Systems
• /
• v.8 no.2
• /
• pp.159-175
• /
• 2002

Web mining is an emerging science of applying modem data mining technologies to the problem of extracting valid, comprehensible, and actionable information from large databases of web in e-Business environment and of using it to make crucial e-Business decisions. In this paper, we present the noble framework of data visualization system based on web mining for analyzing the characteristics of on-line customers in e-Business. We also propose the framework of forecasting system for providing the forecasting information of sales/purchase through the use of web mining based on artificial intelligence techniques such as back-propagation network, memory-based reasoning, and self-organizing map.

• Knowledge Management Research
• /
• v.24 no.3
• /
• pp.127-148
• /
• 2023

Traditional Business Intelligence environment is limited to support the rapidly changing businesses and the exponential growth of data in both volume and complexity of data. Companies should shift their business intelligence environment into Self-Service Business Intelligence (SSBI) environment in order to make smarter and faster decisions. However, firms seem to face various challenges in implementing and leveraging the effective business intelligence system, and academics do not provide sufficient studies related including the success factors of SSBI. This study analyzes the three cases of Korean companies in depth, their development process and the assessment of business intelligence, based on the theoretical model on the key success factors of business intelligence systems. The comparative analysis of the three cases including project managers' interviews and performance evaluations provide rich implications for the successful adoption and the use of business intelligence systems of firms. The study is expected to provide useful references for firms to fully leverage the effects of business intelligence systems and upgrade towards self-service business intelligence systems.

• Journal of Digital Convergence
• /
• v.11 no.8
• /
• pp.119-125
• /
• 2013

The Recently many companies have tried to implement the Business Intelligence (BI) system to enhance the competitive edge in the rapid change of business environment. The BI system is implemented on the basis of current Management Information System, like Enterprise Resource Planning (ERP) system. For the successful implementation of BI system, many critical factors, like maturity and satisfaction level of current Information System, should be considered. The goal of this paper is to analyze which factors influence on the implementation intention of BI system, and how is the relationship among these factors. To achieve this goal, the empirical research has been carried out with factor analysis and Structural Equation Model (SEM). The result of this paper could be usefully referred in decision making process for the successful implementation of the BI system, and show the guideline to the management of the companies, which have the plan for the implementation of BI system.

• Korean Journal of Artificial Intelligence
• /
• v.12 no.1
• /
• pp.25-29
• /
• 2024

In this study, research was conducted to predict the probability of cervical cancer occurrence associated with the use of hormonal contraceptives. Cervical cancer is influenced by various environmental factors; however, the human papillomavirus (HPV) is detected in 99% of cases, making it the primary attributed cause. Additionally, although cervical cancer ranks 10th in overall female cancer incidence, it is nearly 100% preventable among known cancers. Early-stage cervical cancer typically presents no symptoms but can be detected early through regular screening. Therefore, routine tests, including cytology, should be conducted annually, as early detection significantly improves the chances of successful treatment. Thus, we employed artificial intelligence technology to forecast the likelihood of developing cervical cancer. We utilized the logistic regression algorithm, a predictive model, through Microsoft Azure. The classification model yielded an accuracy of 80.8%, a precision of 80.2%, a recall rate of 99.0%, and an F1 score of 88.6%. These results indicate that the use of hormonal contraceptives is associated with an increased risk of cervical cancer. Further development of the artificial intelligence program, as studied here, holds promise for reducing mortality rates attributable to cervical cancer.

• International journal of advanced smart convergence
• /
• v.8 no.2
• /
• pp.56-67
• /
• 2019

The aim of this study is to develop Artificial Intelligence (AI) based business models of media firms. We define AI and discuss 'AI activity model'. The practices of the efficiency model are home equipment-based personalization and media content recommendation. The practices of the expert model are media content commissioning, content rights negotiation, copyright infringement, and promotion. The practices of the effectiveness model are photo & video auto-tagging and auto subtitling & simultaneous translation. The practices of the innovation model are content script creation and metadata management. The related use cases from 2012 to 2017 are introduced along the four activity models of AI. In conclusion, we propose for media companies to fully utilize the AI for transforming from traditional to successful digital media firms.

• ETRI Journal
• /
• v.46 no.3
• /
• pp.501-512
• /
• 2024

With an explosive increase of data produced annually, researchers have been attempting to develop solutions for systems that can effectively handle large amounts of data. Single-operating-system (OS) non-uniform memory access (NUMA) abstraction technology is an important technology that ensures the compatibility of single-node programming interfaces across multiple nodes owing to its higher cost efficiency compared with scale-up systems. However, existing technologies have not been successful in optimizing user performance. In this paper, we introduce a single-OS NUMA abstraction technology that ensures full compatibility with the existing OS while improving the performance at both hypervisor and guest levels. Benchmark results show that the proposed technique can improve performance by up to 4.74× on average in terms of execution time compared with the existing state-of-the-art opensource technology.

• Journal of Software Assessment and Valuation
• /
• v.17 no.2
• /
• pp.59-73
• /
• 2021

Recently, artificial intelligence has spread rapidly and popularized and expanded to the voice recognition personal service sector, and major countries have established artificial intelligence promotion strategies, but in the case of South Korea's defense domain, its influence is low with a geopolitical location with North Korea. This paper presents a total of six strategies for promoting South Korea's defense artificial intelligence, including establishing roadmaps, securing manpower, installing the artificial intelligence base, and strengthening cooperation among stakeholders in order to increase the impact of South Korea's defense artificial intelligence and successfully promote artificial intelligence. These suggestions are expected to establish the foundation for expanding the base of artificial intelligence.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.1
• /
• pp.119-124
• /
• 2022

Successful underwater localization requires a large-scale, parallel computing environment that can be mounted on various underwater robots. Accordingly, we propose a design method for an artificial intelligence computing platform for underwater localization. The proposed platform consists of a total of four hardware modules. Transponder and hydrophone modules transmit and receive sound waves, and the FPGA module rapidly pre-processes the transmitted and received sound wave signals in parallel. Jetson module processes artificial intelligence based algorithms. We performed a sound wave transmission/reception experiment for underwater localization according to distance in an actual underwater environment. As a result, the designed platform was verified.

• Asian Journal of Innovation and Policy
• /
• v.5 no.3
• /
• pp.330-342
• /
• 2016

This is an interview with Professor Kwang-Hyung Lee, founding Dean of KAIST Moon Soul Graduates School of Future Strategy and founder of the Department of Bio and Brain Engineering of the same university casting two questions about academics. The first question is what pattern is desirable in the evolution of research topics of an academics. While traditional researchers in science and engineering tend to focus on one subject in ever greater depth over time, Professor Lee's research agenda has spanned several new topics by gradually changing the content of the study: from artificial intelligence to bio and brain research, and to creativity development method, further to future study. The second question is about researchers' social responsibility. He has devoted to contributes to industry fields and the nation through academic activities as well as educating several successful business people, founding a new academic department and graduate school of future studies.

• Journal of Information Technology Services
• /
• v.11 no.sup
• /
• pp.165-176
• /
• 2012

Context-Awareness system provides an appropriate service to user by recognizing situation from surrounding environment. There are many successful studies on this framework, but still has some limitations. In this paper, we are describing a context-awareness middleware that can enhance the limitation of the previous approaches. We first defined a new concept of context-awareness environment as a social intelligence. This concept implies that intelligent objects can make relationships, can aware of situation from surrounding environment, and can collaborate to accomplish a given task. The significance of the study is as follows. First, the system is capable of multi context-awareness since it is designed with a structure that supports multiple lines of reasoning. Second, the system is capable of context planning by adapting AI planning mechanism. Third, the system is capable of making the intelligent objects as a group for collaboration, and provides adaptive service to user. We have developed a prototype of the system and tested with a virtual scenario.