重要信息

会议网址：www.iwbdc.org

会议时间：2023年11月17-19日

召开地点：中国西安

截稿时间：2023年10月20日

录用通知：投稿后2周内

收录检索：EI,Scopus

主办单位：湖南大学、武汉大学、湖南省生物信息学会

Committee

General Chairs
Yi Pan Shenzhen Institute of Advanced  Technology Chinese Academy  of Sciences, China	Xiaohua Hu Drexel University, USA
Conference Chairs
Shaoliang Peng Hunan University, China	Weiwei Liu Wuhan University, China
Program Chairs
Chi Man PUN University of Macau, China	Hebah H . O. Nasereddin Middle East University, Jordan	Xiaofeng Ding Huazhong University of Science  and Technology, China
Program Committee
L. M. Patnaik Indian Institute of Science, India	Massimo Marchiori University of Padua, Italy

Publication Chair

 Alfredo Cuzzocrea

 University of Calabria, Italy

Publicity Chair

 Xiuwen Gong

 The University of Sydney, Australia

WBDC 2023 Speakers

Keynote Speaker Ⅰ

Professor Axel-Cyrille Ngonga Ngomo

Paderborn University, Germany

Biography: Axel holds a Ph.D and habilitation in Computer Science from Leipzig University, Germany. He is currently a Full Professor for Data Science at Paderborn University, where he leads the DICE group. The group focuses on both foundational and applied research all along the lifecycle of knowledge graphs. Hence, it has developed a plethora of algorithms and platforms for knowledge extraction, integration, fusion, and application in intelligent systems. DICE’s research has attracted several international research prizes including best paper awards at top conferences such as ISWC and ESWC. Moreover, Axel is the grateful recipient of several prestigious fellowships for his research, including Northrhine Westphalia’s 2023 Lamarr Fellowship. In his talk, Axel will present some of his recent work on machine learning on knowledge graph with a focus on scalability and explainability. 

Speech Title: Scaling up hybrid learning on knowledge graphs 

Abstract: Knowledge graphs are an increasingly popular family of data structures for knowledge representation, of which some are endowed with explicit semantics. While learning on graphs is becoming increasingly more popular and scalable, learning on (semantically rich) knowledge graphs is significantly more difficult to achieve. In this talk, we will present recent results on achieving time-efficient and accurate learning on knowledge graphs. We will begin by giving a brief introduction to the class expression learning problem, a supervised learning task on knowledge graphs. We will build upon refinement operators and the corresponding learning principles to derive novel, increasingly more scalable approaches to learning on knowledge graphs while respecting their semantics. 

Invited Speaker Ⅰ

Associate Professor Hao Li

IEEE member

Xidian University, China

Biography: Hao Li is an Associate Professor at the School of Electronic Engineering, Xidian University. He received the B.Eng. degree in electronic engineering and the Ph.D. degree in pattern recognition and intelligent systems from Xidian University, Xi’an, China, in 2013 and 2018, respectively. His major research interests include computational intelligence, machine learning and remote sensing image understanding. He was a recipient of the Young Distinguished Talent in Shaanxi, China and the Young Talent of University Association for Science and Technology in Shaanxi, China. He received the Outstanding Doctoral Dissertation Award in Shaanxi, China and the Best Student Paper Award at the International Conference on CIS. He is an IEEE member and serves as a member of IEEE Neural Networks Technical Committee.

会议简介

★2023年第四届大数据与计算国际会议（WBDC 2023）---Ei Compendex＆Scopus-Call for papers

｜2023年11月17-19日,中国西安｜网址: www.iwbdc.org

★WBDC 2023将围绕“大数据与计算”研究领域而展开，来自世界各地的主要研究人员和行业专家将通过论文和口头报1告介绍研究成果。本次会议由香港机器人与自动化协会（HKSRA）主办，将于2023年11月17-19日在中国西安召开，在会议期间您将有机会聆听到前沿的学术报告，见证该领域的成果与进步。

会议日程预览：

关于出版和索引

所有接受的论文将在线出版至会议论文集，将被Ei Compendex，SCOPUS，Google Scholar，Cambridge Scientific Abstracts（CSA），Inspec， ISTP等检索，优秀论文将在国际期刊上发表。

征稿主题/会议征稿

算法、实验、原型和实现、实时大数据系统的应用与评价、自主计算和网络基础设施、大数据算法、应用和服务、大数据分析和机器与深度学习、政府、公共部门和社会的大数据分析、中小企业大数据分析、大数据应用、大数据架构、大数据服务、大数据教育、改善弹性基础设施的大数据、社交网络大数据、大数据行业标准

更多征稿主题请访问： http://www.iwbdc.org/cfp.html

投稿方式

CMT在线投稿：https://cmt3.research.microsoft.com/WBDC2023

请作者按照官网模板格式进行排版。排版好的论文全文（word+pdf版）发送至CMT在线系统。

投稿注意事项：

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提交全文：即做参会做报告，并且出版文章；

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