Startup success prediction in the AI industry = 인공지능 산업에서의 스타트업 성공 예측

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As Artificial intelligence is used in various industries, the necessity of AI research at the enterprise level is emerging. According to this trend, companies using AI are showing a sharp increase and M&A of large companies is increasing rapidly. As a result, venture companies that are challenging start-ups and existing companies that want to introduce AI are looking at startups that use artificial intelligence to jump into the AI industry. In this paper, a successful prediction model for startups with artificial intelligence through data analysis. The success forecasting model will help startups and investors gain a better understanding of the success of high-risk startups in this latest trend. Examine Crunchbase's database of the largest start-up data in the United States and accurately classify which startups are successful by building a predictive model through supervised learning using data from all startups with AI, not just in one country. With advances in information technology, robust machine characterization using complex machine learning algorithms can provide reliable results for data analysis. The success prediction model proposed in this study achieves a 95% forecast rate and the capacity to predict success is a very important competitive advantage for companies seeking to absorb venture capital and AI because they can see ahead of potential companies from an investment perspective.
Advisors
Kim, Wonjoonresearcher김원준researcher
Description
한국과학기술원 :기술경영학부,
Publisher
한국과학기술원
Issue Date
2020
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 기술경영학부, 2020.2,[ii, 24 p. :]

Keywords

Startup▼aSuccess▼aPrediction▼aAI▼aArtificial Intelligence; 스타트업▼a성공▼a예측▼a인공지능

URI
http://hdl.handle.net/10203/283989
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=910781&flag=dissertation
Appears in Collection
MG-Theses_Master(석사논문)
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