Abstract
Big data is the most talked about topic in recent years. Whether it is the Internet of things, cloud computing, smart city or artificial intelligence, it is closely related to big data technology. Big data has created great value to the economy and society. For example, the United States combines big data with medical system and develops intelligent infusion set under big data analysis, which brings great convenience to medical staff. Big data can also be used in innovative undertaking, which plays a great role in the cultivation of undergraduate’ entrepreneurial quality. The purpose of this document is to discuss the implementation of large data analyses on the culture of innovation and the business quality of undergraduate, to analyse the opportunities and challenges faced by students and to help students make rational use of innovation and the entrepreneurial spirit of large data. The main content of this paper is, first of all, using the questionnaire survey method to understand the current situation of undergraduate’ entrepreneurship, looking for the problems existing in undergraduate’ entrepreneurship. Finally, it explains how to use clustering algorithm and big data platform to mine network data, extract the key information of user needs, and how to help undergraduate seize the opportunity of entrepreneurship. According to research, generally speaking, undergraduate rarely participate in the social practice of innovative undertaking, only 10.15% of them really understand the entrepreneurial knowledge, and only 4.63% of them have the ability to develop and explore the market. Therefore, during their study in Colleges and universities, they should be encouraged to start their own businesses more spiritually and financially.
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Xiong, Y. (2022). The Application of Big Data Analysis in the Cultivation Path of Undergraduate’ Innovative Undertaking Quality. In: Pei, Y., Chang, JW., Hung, J.C. (eds) Innovative Computing. IC 2022. Lecture Notes in Electrical Engineering, vol 935. Springer, Singapore. https://doi.org/10.1007/978-981-19-4132-0_77
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DOI: https://doi.org/10.1007/978-981-19-4132-0_77
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