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

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.225-234
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• 2000

기존의 인터넷 비즈니스를 분류하는 분류법이 인터넷 비즈니스의 특성을 규명하고 새로운 인터넷 비즈니스를 고안하는 데는 적합한 방법이지만 기업들에게 의미 있는 경영전략을 제시하는 데에는 어려움이 있다. 이에 새로운 분류기준으로 인터넷 기업들을 분류하고 경영 전략적인 측면에서 시사하는 바를 알아본 후, 성과모형을 개발하여 인터넷 기업들에게 바람직한 비즈니스 유형을 규명하였다. 또한 인터넷 비즈니스의 핵심 성공요인을 도출하여 향후 기업들이 본 연구 결과를 통해서 기업 성과 증진에 도움을 줄 것으로 기대한다.

• Journal of Intelligence and Information Systems
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• v.14 no.3
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• pp.87-108
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• 2008

Recently, commerce paradigm is developing to e-commerce, mobile commerce, and ubiquitous commerce(u-commerce). While many companies consider to adopt u-commerce, they have a task to solve this problem. The typical consideration is to derive the critical success factors for u-commerce. By the literature survey, this paper suggests the critical success factors for e-commerce business and off-line business to transform to u-commerce environment. We find significant variables to contribute the management performance by analyzing the cause and effect relationship.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.9
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• pp.363-370
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• 2022

Grasping a target object among clutter objects without collision requires machine intelligence. Machine intelligence includes environment recognition, target & obstacle recognition, collision-free path planning, and object grasping intelligence of robot hands. In this work, we implement such system in simulation and hardware to grasp a target object without collision. We use a RGB-D image sensor to recognize the environment and objects. Various path-finding algorithms been implemented and tested to find collision-free paths. Finally for an anthropomorphic robot hand, object grasping intelligence is learned through deep reinforcement learning. In our simulation environment, grasping a target out of five clutter objects, showed an average success rate of 78.8%and a collision rate of 34% without path planning. Whereas our system combined with path planning showed an average success rate of 94% and an average collision rate of 20%. In our hardware environment grasping a target out of three clutter objects showed an average success rate of 30% and a collision rate of 97% without path planning whereas our system combined with path planning showed an average success rate of 90% and an average collision rate of 23%. Our results show that grasping a target object in clutter is feasible with vision intelligence, path planning, and deep RL.

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

• Korean Journal of Culture and Social Issue
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• v.11 no.1
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• pp.157-180
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• 2005

Successful Intelligence (SI) developed by R. Sternberg has impacted on various fields such as education and industry, providing with intuitive view-points concerning the definition, nature, and measurement of intelligence. It would be a timely work to review how SI has been progressed, what contributions it made, what it has influenced on intelligence research in Korea, and what the implications of SI for future research are. With that in mind, this review is composed of several sections. First, an overview of the SI's historical development and main characteristics and contributions is presented with three distinct periods: Era of the Componential Theory, of Triarchic Theory, and of Successful Intelligence. Second, Selected researches conducted in Korea based on SI are summarized. Lastly, future research for validation of SI is discussed.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.116-121
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• 2006

삶의 질을 높여주기 위한 지능적이고 자율적인 컴퓨팅이 uT 환경과 더불어 일상생활에 스며들고 있다. uT 환경을 성공적으로 정착시키기 위해서는 다양한 사람들과 지능적인 개체들이 조직화되어 조직내부 구성원들과 조직들이 서로 커뮤니케이션을 수행하며 지역적이고 전역적인 목표를 달성하여야 한다. 본고에서는 커뮤니티 컴퓨팅의 개념과 가상 시나리오의 모의실험을 수행하는 시뮬레이터를 이용하여 uT 환경 구성의 초석을 다지고자 한다.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.19-29
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• 2020

As the AI speaker market is growing rapidly in recent years, the competition for the preoccupation of children who are the main users and the future prospective customers of the related companies is very intense. However, there is a lack of empirical research on how children interact with AI speakers. Therefore, this research examines the interactions between children and AI speakers, primarily through field studies, to extract what functions they use and what features they have. For this purpose, 799 conversations were collected and analyzed using the log data of the AI speaker recorded in real time. As a result, children were more likely to use children's songs, fairy tales, emotional conversations, and personification compared to adults. In addition, content analysis by specific types resulted in success/failure cases of interaction between children and AI speakers and proposed improvements by failure type. This study is meaningful in that it identifies children's AI speaker preferences, content, and major conversation patterns, and provides guidelines for developing services that meet children's eye level.

• Journal of the KSME
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• v.44 no.4
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• pp.59-62
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• 2004

정보서비스를 제공해 주는 로봇이나 오락용 로봇과 같은 인공지능 로봇이 사업화에 성공하기 위해서 간과할 수 없는 중요한 요인들이 많이 있다. 로봇과 사용자간에 자연스럽게 이루어지는 상호작용이나 로봇의 특성을 효과적으로 살려 줄 수 있는 컨텐츠는 사업화 성공의 관점에서 볼 때 중요한 요인이 될 수 있을 것이다. 로봇이 가지고 있는 입력과 출력을 효율적으로 연계하여 제어함으로써 로봇이 사용자와 보다 자연스럽고 친화적인 상호교류가 가능해질 수 있다.(중략)

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.327-351
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• 2023

This paper aims to derive success factors that successfully lead an artificial intelligence (AI) project and prioritize importance. To this end, we first reviewed prior related studies to select success factors and finally derived 17 factors through expert interviews. Then, we developed a hierarchical model based on the TOE framework. With a hierarchical model, a survey was conducted on experts from AI-using companies and experts from supplier companies that support AI advice and technologies, platforms, and applications and analyzed using AHP methods. As a result of the analysis, organizational and technical factors are more important than environmental factors, but organizational factors are a little more critical. Among the organizational factors, strategic/clear business needs, AI implementation/utilization capabilities, and collaboration/communication between departments were the most important. Among the technical factors, sufficient amount and quality of data for AI learning were derived as the most important factors, followed by IT infrastructure/compatibility. Regarding environmental factors, customer preparation and support for the direct use of AI were essential. Looking at the importance of each 17 individual factors, data availability and quality (0.2245) were the most important, followed by strategy/clear business needs (0.1076) and customer readiness/support (0.0763). These results can guide successful implementation and development for companies considering or implementing AI adoption, service providers supporting AI adoption, and government policymakers seeking to foster the AI industry. In addition, they are expected to contribute to researchers who aim to study AI success models.