Heterogeneous Data Analytics in the Era of LLM and Big Data

报告题目: Heterogeneous Data Analytics in the Era of LLM and Big Data
报告人:Xiaozhong Liu
时间:6月19日(周一) 下午3:00—5:00

报告摘要:Heterogeneity is one of the major features and challenges of big data and heterogeneous data result in problems in data integration and Big Data analytics. A number of applications, e.g., NLP, graph mining and pandemic preparedness prediction, have been explored by leveraging heterogeneous data mining. In this talk, I will present our recent investigations to address this work, including large scale knowledge graph mining for NLP and eCommerce data mining with different types of user data. We will also explore heterogeneous data mining opportunities with LLM support.

报告人简介:Xiaozhong Liu is an Associate Professor from Data Science and Computer Science at Worcester Polytechnic Institute. He also serves as senior consultant to Alibaba DAMO Academy, the research arm of Alibaba, and leads large-scale NLP projects. He has published more than 150 papers in leading computer science conferences and information science journals, e.g, PNAS, JASIST, AAAI, SIGIR, IJCAI, EMNLP, ACL and WWW, and holds nine patents in AI and NLP. His areas of research interest include Data Science, NLP, Explainable AI, Graph Mining, Cybercrime and Security, and Computational Social Science. Currently, his algorithm APIs are called more than 170 million times per day on different active eCommerce and Web Search platforms and effectively outperforms predecessor methods by 10% on average.


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