2018 IEEE International Conference on Big Knowledge ICBK

活动简介

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 draws researchers 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.

征稿信息

重要日期

2018-06-20

初稿截稿日期

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, and privacy.
Applications and services of big knowledge in all domains including web, medicine, education, healthcare, and business.
- Big Health Care Decision Making
- Crowdsourcing
- 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