报 告 人：王晖教授
英国Ulster大学
报告题目：Toward Machine Understanding
时 间：
地 点：仓山校区成功楼603报告厅
参加对象：计算智能教研室全体教师和部分数据挖掘方向研究生
报告摘要：
Big Data is a hot term used to characterise today’s digital world. Data is being generated in large quantity and velocity, and data is complex due to variety – from structured (e.g. measurements), semi-structured (e.g. web pages), to unstructured (e.g. text, video). One of the challenges Big Data presents is how to get machines to understand data. If we could understand text, we could summarise it or answer questions. If we could understand video, we could detect events for surveillance purpose.
Machine Understanding is an emerging field of study that is aimed at tackling the challenging problem of getting machines to understand data in a modern way, one that utilises recent advances in areas such as computational semantics and ontology, focuses on common `understanding’ operations that can be specialised for different types of data.
In this talk, Professor Hui Wang will present his work on knowledge-supported learning as an approach to machine understanding. He will demonstrate a journey from Lattice Machine to Contextual Probability to Neighbourhood Counting Kernel, leading to a new approach to machine learning where learning from data is supported by existing knowledge. He will then present a case study on machine understanding in the context of a project.
专家简介：
王晖分别于1985年，1988年在吉林大学计算机科学与技术学院获学士，硕士学位，于1996年在英国Ulster大学获博士学位。从1988年起至1993年在吉林大学任教。1996年在Ulster大学取得博士学位后留校任教。1996-2002在Ulster大学担任讲师（lecturer），2002-2006担任高级讲师(senior lecturer)，2006-2011担任副教授(reader),2011至今任教授。从2009年9月起任Ulster大学知识和数据工程研究室主任。王晖教授长期从事机器学习，人工智能和知识工程，数据挖掘等领域的研究工作，他的很多原创性的工作，包括格子机学习方法、Neighbourhood Counting Kernel的相似度测量方法，在国际上得到认可并获得广泛关注。近5年独立承担欧盟基金项目（EU FP7） 3项，约80万英镑，英国投资北爱尔兰研发基金 Invest Northern Ireland R&D Programme，约35万英镑，以及英国皇家学会与中国自然科学基金等科研项目多项。近5年发表SCI 1区文章1篇，SCI 2区文章 6篇，SCI 3区文章3篇。 王晖教授还兼任国际期刊 IEEE Transactions on SMC-B，International Journal of Machine Learning and Cybernetics副主编，以及多个国际会议的大会共同主席。
