报告名称：A discrete dynamics approach to sparse calculation and applied in ontology science

报告专家：张运清

专家所在单位：南京大学

报告时间：2022年4月24日10：00-12：00

报告地点:腾讯会议（会议号：536756642）

专家简介：张运清，南京大学数学系教授。2007年于南京大学数学系获得博士学位。主要从事极值图论、结构图论、组合优化的理论及应用等方面的研究。主持和参与承担多项国家自然科学面上项目以及国际合作基金项目.

报告摘要：In the era of big data, with the increase of data processing information and the increase of data complexity, higher requirements are put on the tools and algorithms of data processing. As a tool for structured information representation, ontology has been used in engineering fields such as chemistry, biology, pharmacy, and materials. As a dynamic structure, the increasing concepts contributes to a gradual increase of a single ontology. In order to solve the problem of computational complexity decreasing in the procedure of similarity calculating, the techniques of dimensionality reduction and sparse computing are applied to ontology learning.