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【青椒学术沙龙】知识图谱——人工智能的基石
发布时间:2019-10-09    

时间:2019年10月11日(周五)中午12点30分

地点:北洋园校区50楼A333教工活动中心(咖啡厅)

报告题目:知识图谱——人工智能的基石

主讲人:王鑫

【个人简介】

王鑫,天津大学智能与计算学部副教授、人工智能学院副院长。2009年和2004年于南开大学计算机科学与技术系分别获工学博士和学士学位,澳大利亚西澳大学、格里菲斯大学访问学者。中国计算机学会高级会员、信息系统专业委员会秘书长、计算机术语审定工作委员会执行委员、数据库专业委员会委员、大数据专家委员会通讯委员;中国中文信息学会语言与知识计算专业委员会委员;中国人工智能学会教育工作委员会委员;ACM 会员、IEEE会员。主要研究方向为知识图谱数据管理与学习、大规模图数据库、大数据分布式处理。主持国家自然科学基金项目、天津市自然科学基金项目、“百度主题研究”项目、“CCF-华为数据库创新研究计划”等项目。在IEEE TPDS, Complexity, WWW, ICDE, CIKM, ISWC, ER等国内外学术期刊和会议上发表论文70多篇。国际会议APWeb-WAIM2020程序委员会主席,JIST2019程序委员会主席、DASFAA2018宣传主席以及WWW2019, KDD2019, ISWC2019, DASFAA2017~2019, WISE2018~2019等国际会议程序委员会委员。获得国际会议APWeb-WAIM2018最佳论文提名奖和最佳演示论文奖。SCI期刊Big Data Research编委、中文核心期刊《计算机工程与应用》、《计算机系统应用》编委,IEEE TKDE、KBS、WWWJ等国际期刊审稿人。

【报告内容简介】

知识图谱是人工智能的重要基石,其包括知识获取、知识组织、知识存储、知识查询与检索、知识推理与应用等方面,是人工智能符号主义学派的新发展,是解决人工智能可解释性难题的关键工具。本报告在给出人工智能历史背景之后,追溯知识图谱的发展脉络,包括知识表示方法和知识工程的发展,主要介绍目前以语义万维网和关联数据为代表的主流知识图谱理论、技术、标准与应用,展望知识图谱如何促进新一代人工智能的发展。

【相关学科】人工智能、计算机、软件工程、图书情报

【主办单位】校工会、图书馆、科研院、校青年教师联谊会

Lecture: Knowledge Graphs—the Cornerstone of AI

When: 12:30 p.m., Friday, October, 11th, 2019

Where: A333, 50th Building, School of Chemical Engineering and Technology, Beiyang campus

Lecturer:

Xin Wang is an Associate Professor at College of Intelligence and Computing and the vice-dean of School of Artificial Intelligence, Tianjin University. He obtained his Ph.D. and Bachelor degrees in Computer Science from Nankai University in 2009 and 2004, respectively, and worked as a visiting scholar at the University of Western Australia and Griffith University. He is a senior member of China Computer Federation (CCF), and the secretary-general of CCF Technical Committee on Information Systems, a member of CCF Technical Committee on Databases. His research interests include knowledge graph data management and learning, large-scale graph databases, and big data processing. He has been the main investigator of two research projects funded by the National Natural Science Foundation of China (NSFC). He has published more than 70 research papers in various international conferences and journals, including ICDE, WWW, CIKM, ISWC, ER, IEEE TPDS, and Complexity. He served as a PC co-chair of APWeb-WAIM’20, PC co-chair of JIST’19, a publicity co-chair of DASFAA’18, and PC members of WWW’19, KDD’19, ISWC’19, DASFAA’17-’19, WISE’18-’19, etc. He won the best paper runner-up award and the best demo paper award in APWeb-WAIM2018. He is an editor of the SCI journal Big Data Research, reviewer of international journals including IEEE TKDE, KBS, WWWJ, etc.

About the Lecture:

Knowledge Graph is the cornerstone of Artificial Intelligence, which includes knowledge acquisition, knowledge organization, knowledge storage, knowledge query and retrieval, knowledge reasoning and application, etc, which is the new development of Symbolic Artificial Intelligence, which is a key tool to solve the interpretability problem of AI. This talk will first give the historical background of Artificial Intelligence, then track back the development of knowledge graphs, which includes the approaches of knowledge representations and development of knowledge engineering, then mainly introduce the current mainstream theories, methods, standards, and applications of knowledge graphs, which is represented by the Semantic Web and Linked Data, and finally look forward to how knowledge graphs promote the development of the next generation of AI.

Relevant Discipline: Artificial Intelligence, Computer Science, Software Engineering, Library and Information

Organizers: Trade Unions, Library, Office of Science and Technology, Young Teachers Association

All students and staff of Tianjin University are welcome.

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