• 반도체디스플레이기술학회지
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• 제21권3호
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• pp.69-73
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• 2022

The application of cloud computing to many industrial domains is rapidly increasing, and domestic and foreign cloud service providers are actively conducting business. In the domestic cloud market, it is necessary to establish an ecosystem with partner operators that work closely with private cloud service providers. In this paper, to create such an environment, we propose a framework that can evaluate the capabilities of partners required for cloud service providers to establish specific business strategies. The framework proposed in this study establishes criteria for evaluating partners' competencies and applies a decision-making model such as fuzzy AHP for evaluation. Eventually this will help not only to expand the domestic cloud market but also to strengthen the competitiveness of domestic cloud partners through the growth of the domestic cloud market.

• 반도체디스플레이기술학회지
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• 제20권2호
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• pp.115-120
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• 2021

In Korea, where the world's first cloud computing development law was created, cloud service technology has been developing so far, and the industries to which artificial intelligence and big data technologies can be applied based on this are increasing. It is important for domestic and overseas cloud operators to secure many partners in order to provide optimal services to users. It is also important to systematically develop the partner's technology and discover new partners. In particular, the public, medical, and financial sectors are industrial fields that are difficult for domestic as well as global cloud service providers to expand without the help of partners. This study analyzes partner policies for industries caused by domestic regulations through domestic and foreign cases, and aims to establish partner management policies optimized for the domestic environment.

• ETRI Journal
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• 제32권4호
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• pp.634-637
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• 2010

This letter presents a model for a dynamic collaboration (DC) platform among cloud providers (CPs) that prevents adverse business impacts, cloud vendor lock-in and violation of service level agreements with consumers, and also offers collaborative cloud services to consumers. We consider two major challenges. The first challenge is to find an appropriate market model in order to enable the DC platform. The second is to select suitable collaborative partners to provide services. We propose a novel combinatorial auction-based cloud market model that enables a DC platform among CPs. We also propose a new promising multi-objective optimization model to quantitatively evaluate the partners. Simulation experiments were conducted to verify both of the proposed models.

• 한국빅데이터학회지
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• 제2권2호
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• pp.9-16
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• 2017

클라우드 서비스에 기반한 글로벌 플랫폼 솔루션 기업은 인공지능과 빅데이터 서비스를 킬러앱으로 발전시키며 기업의 산업 솔루션을 제공하며 이것은 기업의 비즈니스 밸류 체인에 큰 변화를 가져오게 할 것이다. 제조 생산의 최적화에서 디자인과 마케팅, 유통 등이 중요해 지고 SCM와 고객 데이터가 수평적으로 연결되어 관리가 필요해지면서 기업의 모든 데이터도 하나의 플랫폼을 중심으로 데이터에 기반한 통합을 이루어 기업 의사 결정 모델을 구현하는 방향으로 발전하게 된다. 이러한 변화는 기업의 소셜, 모발 솔루션과 통합되는 디지털 혁신을 리드하고 있다. 또한 기업은 다른 기술 경쟁력을 가진 기업의 기술, 플랫폼 솔루션과 Ecosystem 비즈니스 파트너로 융합하여 새로운 비즈니스 모델을 만들고 산업과 지역의 경계를 넘어 새로운 에코시스템 마켓플레이스를 만들고 있다.

• 의학교육논단
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• 제18권2호
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• pp.51-57
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• 2016

This literature review explores artificial intelligence (AI) technology trends and IBM Watson health and medical references. This study explains how healthcare will be changed by the evolution of AI technology, and also summarizes key technologies in AI, specifically the technology of IBM Watson. We look at this issue from the perspective of 'information overload,' in that medical literature doubles every three years, with approximately 700,000 new scientific articles being published every year, in addition to the explosion of patient data. Estimates are also forecasting a shortage of oncologists, with the demand expected to grow by 42%. Due to this projected shortage, physicians won't likely be able to explore the best treatment options for patients in clinical trials. This issue can be addressed by the AI Watson motivation to solve healthcare industry issues. In addition, the Watson Oncology solution is reviewed from the end user interface point of view. This study also investigates global company platform business to explain how AI and machine learning technology are expanding in the market with use cases. It emphasizes ecosystem partner business models that can support startup and venture businesses including healthcare models. Finally, we identify a need for healthcare company partnerships to be reviewed from the aspect of solution transformation. AI and Watson will change a lot in the healthcare business. This study addresses what we need to prepare for AI, Cognitive Era those are understanding of AI innovation, Cloud Platform business, the importance of data sets, and needs for further enhancement in our knowledge base.