SS8:Knowledge-driven Big Data Computing and Its Applications         

·   Organizers

Ling Wang, Northeast Electric Power University, China - smile2867ling@neepu.edu.cn, Keun Ho Ryu, Chungbuk National University, Republic of Korea - khryu@chungbuk.ac.kr, Lei Kou, Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), China- koulei1991@qlu.edu.cn, Wei Ding, Shandong Computer Science Center (National Supercomputer Center in Jinan) - dingw@sdas.org and Teng Li, Shandong University, China - li.teng@sdu.edu.cn

·   Description/Abstract

Knowledge Driven is uplevel computing of basic big data, which aims to construct a sustainably knowledge upgraded structure by valuable rules discovery continuously. It can support more complex knowledge decisions through more widely knowledge cross computation, such as understandability interaction, potential valuable relevance mining, interest-aware computing, and etc. This special session will discuss recent advanced in knowledge-driven big data computing and its applications.

The topics of interest include, but are not limited to:

• Knowledge-driven Data Mining and Machine Learning Models
• Potential Knowledge Mining based on Semantic Analysis
• Bioinformatics and EBM Decision Making
• Renewable Energy Models and Prediction
• Spatial Temporal Data Mining and Knowledge Extraction
• Physical Model and Knowledge-driven Integrated Learning
• Sensor-aware Human-Computer Knowledge Interaction
• Knowledge-driven Chat GPT and AI Interaction
• Smart Grid and Microgrids Resilience Computing
• Trustworthy Decision-making Support for Operation and Maintenance of Wind Farm