Call for Papers
Aims and Scope
Big Knowledge deals with fragmented knowledge from heterogeneous, autonomous information sources for complex and evolving relationships, in addition to domain expertise. The IEEE International Conference on Big Knowledge (ICBK) provides a premier international forum for presentation of original research results in Big Knowledge opportunities and challenges, as well as exchange and dissemination of innovative, practical development experiences. The conference covers all aspects of Big Knowledge,including algorithms, software, systems, and applications. ICBK drawsresearchers and application developers from a wide range of Big Knowledge related areas such as knowledge engineering, big data analytics, statistics,machine learning, pattern recognition, data mining, knowledge visualization,high performance computing, and World Wide Web. By promoting novel, high quality research findings, and innovative solutions to challenging Big Knowledge problems, the conference seeks to continuously advance the state-of-the-art in Big Knowledge.
Accepted papers will be published in the conference proceedings by the IEEE Computer Society. Awards will be conferred at the conference on the authors of the best paper and the best student paper. A selected number of best papers will beinvited for possible inclusion, in an expanded and revised form, in the Knowledge and Information Systems Journal.
Topics of Interest
Topics of interest include, but are not limited to:
• Foundations,algorithms, models, and theory of big knowledge processing.
• Knowledge engineering with big data.
• Machine learning, data mining, and statistical methods for big knowledge science and engineering.
• Acquisition,representation and evolution of fragmented knowledge.
• Fragmented knowledge modeling and online learning.
• Knowledge graphs and knowledge map.
• Topology and fusion on fragmented knowledge.
• Visualization,personalization, and recommendation of big knowledge navigation and interaction.
• Big knowledge systems and platforms, and their efficiency, scalability, andprivacy.
• Applications and services of big knowledge in all domains including web, medicine,education, healthcare, and business.
◦ Big Health Care Decision Making
◦ Crowd sourcing
◦ Data-driven Granular Cognitive Computing
◦ Deep Learning
◦ Edge Computing in Medical Analyticsg
◦ Graph Mining
◦ Intelligent Computing for Big Knowledge
◦ Network and Knowledge Graph Representation Learning
◦ Rule and Relationship Discovery
◦ Safe Data Analytics
Submission Guidelines
Paper submissions should be no longer than 8 pages, in the IEEE 2-column format,including the bibliography and any possible appendices. Submissions longer than 8 pages will be rejected without review. All submissions will be reviewed by the Program Committee on the basis of technical quality, relevance to Big Knowledge, originality, significance, and clarity.
All manuscripts are submitted as full papers and are reviewed based on their scientific merit. The reviewing process is confidential. There is no separate abstract submission step. There are no separate industrial, application, short paper or poster tracks. Manuscripts must be submitted electronically in online submission system.We do not accept email submissions.
LaTeX and Word Templates
To help ensure correct formatting, please use the style files for U.S. Letter as template for your submission. These include LaTeX and Word.
Important Dates
All deadlines are at11:59PM UTC-12.
• Paper submission: June 20, 2018
• Notification of acceptance/rejection: August 20, 2018
• Camera-Ready Papers: September 18, 2018
• Registration Deadline: To be announced
• Conference:November 17-18, 2018
More Information
More information about ICBK 2018 is at http://icbk2018.org/
Organization
Conference Chairs
• Xindong Wu,University of Louisiana at Lafayette
• Ong YewSoon, Nanyang Technological University, Singapore
Program Committee Chairs
• Charu Aggarwal,IBM T. J. Watson Research, USA
• Huanhuan Chen,University of Science and Technology of China, China
Web Chair
• Jia Wu, Macquarie Univeristy, Australia
Finance Chair
• Lei Li,Hefei University of Technology, China
Publicity Co-Chairs
• Huajun Chen,Zhejiang University, China
• TsuyoshiIde, IBM T. J. Watson Research Center, USA
OpenKG.CN
中文开放知识图谱(简称OpenKG.CN)旨在促进中文知识图谱数据的开放与互联,促进知识图谱和语义技术的普及和广泛应用。
点击阅读原文,进入 OpenKG 博客。