2020 International Conference on Computer Science and Management Technology (ICCSMT2020)
Keynote Speaker
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Guest Prof. Feng Liu

Shanghai University of International Business and Economics Research Institute of Artificial Intelligence and Change Management, China

Title: The impact and trend of business intelligence under the collaboration of big data, artificial intelligence, and blockchain technology



As a core tool for decision-making assistance, Business Intelligence (BI) has made a lot of contributions to enterprises and society in digging into the value of data and improving business processing capabilities. However, BI also faces many challenges in the process of technology update and iteration, such as low adoption rate, improper planning, and poor data quality. Therefore, in order to maintain and enhance the application value of BI, it is urgent to carry out technological innovations within the scope of big data: use artificial intelligence to enhance data analysis capabilities, upgrade embedded machine learning algorithms to improve data processing efficiency; use blockchain technology for decentralized storage to reduce business costs and solve data trust issues.

This report will focus on BI entities under the innovative model, and explore the design and possible scenarios of new BI by enabling big data, integrating artificial intelligence and blockchain technology. This report will combine frontier literature in academia and advanced applications in the industry to conduct a comprehensive introduction and extended discussion about BI. BI will further exert its own value in the technical architecture of big data, artificial intelligence and blockchain to promote the development of modern business economy.

Han-Teng Liao.jpg

Associate Professor. Han-Teng Liao 

School of Literature and Media Nanfang College of Sun Yat-sen University, China

Research Area: Internet research and methods; integration of quantitative and qualitative research methods; digital methods; social network analysis; web mining and analysis; API use and analysis; data visualization, etc

研究领域:互联网研究和方法; 整合定量和定性研究方法; 数字方法; 社交网络分析; 网络挖掘和分析; API使用和分析; 数据可视化等

Title:Big Data and Artificial Intelligence for Sustainable Development Research Fronts: Implications for Computer Science and Information Management



Investments and Planning surrounding Big Data and Artificial Intelligence (AI) technology innovations, has become the main agenda for European Green Deal in 2020 for green and digital transformation, but also the key part of the United Nations digital cooperation roadmap to use “big data and artificial intelligence to create “digital public goods in the form of actionable real-time and predictive insights,” including to the efforts to respond to the socioeconomic impacts of COVID-19. No systematic review has been conducted to analyze the research fronts on the topic, despite the need for policy and research. With the strategic purpose to layout an overall roadmap regarding Big Data and AI for Sustainable Development for future research planning, a scientometric study has conducted by identifying and analyzing 717 out of one million articles on Big Data and AI, collected from the Institute for Scientific Information (ISI). By analyzing the core publications, authors, organizations, keywords, funding bodies, and the relationship among them, suggestions are made for Computer Science and Information Management disciplines to conduct interdisciplinary research, industry applications, capacity building, etc. The findings show that the emerging topics include the development of industry 4.0, ESG ratings, etc., for traditional sustainable development issues such as clean production, sustainable consumption, circular economy, etc. Discipline-wise, the interdisciplinary field of Green & Sustainable Science & Technology, advancing Big Data and AI as the new generation of information communication technologies (ICT) research fronts. The findings also show the pivotal role of Chinese and French government funding bodies in leading the international cooperation in the field and the top three journal publications of Sustainability, Journal of Cleaner Production,IEEE Access. Facing the policy and market demand on green and digital transformation, researchers and educators of Computer Science and Information Management disciplines should conduct interdisciplinary research and capacity-building activities, and the research fronts identified by the scientometric findings can be used to identify the opportunities and challenges, including green and sustainable technologies, digital transformation, AI for good, etc. for meaningful and relevant international development and cooperation. The data science methods and literature data flow used by the research, can be further developed to provide timely accessible visualization for policy-makers, innovators and researchers evidence-based insights to make better decisions. To meet the methodological, information and industry need for identifying and tracking research fronts, Computer Science and Information Management disciplines should participate in the roadmapping and innovation planning with better strategic foresights, so as to help steering the digital revolution to combat climate change and advance global sustainability, environmental stewardship, and human well-being.