The International Conference on Intelligent Data Science Technologies and Applications (IDSTA2020) (Online)
Date: Oct 18, 2020 11:00 pm – Oct 22, 2020 11:00 am
Location: Virtual
"The International Conference on Intelligent Data Science Technologies and Applications (IDSTA) is a peer reviewed conference that will advance the Data Science field by giving an opportunity for researchers, engineers, and practitioners to present their latest findings in the field. It will also invite key persons in the field to share their current knowledge and their future expectations for the field. Topics of interest for submission include, but are not limited to:
Business Analytics, Text Analytics, Web Analytics, Data Integrity, Data Privacy and Security, Data Warehouse, Information Integration, Human Behavior Understanding, Data Mining, Semi-Structured and Unstructured Data, Data Fusion, Pattern Recognition, Predictive Modelling, Data Mining, Statistical and Structural Pattern Recognition, Performance Analysis and Evaluation, Evolutionary Computing and Optimization, Feature Selection, Fuzzy Computing, Hybrid Methods, Neural Networks, Deep Learning, Process Mining, Granular Computing, Mobile data, City Data Management, Transparency in Research Data, Data and Information Quality, Data Virtualization, Management of Sensor Data, Semantic Web Technologies, Big Data"
Submitted by Gregory Rigby
on
"The International Conference on Intelligent Data Science Technologies and Applications (IDSTA) is a peer reviewed conference that will advance the Data Science field by giving an opportunity for researchers, engineers, and practitioners to present their latest findings in the field. It will also invite key persons in the field to share their current knowledge and their future expectations for the field. Topics of interest for submission include, but are not limited to:
Business Analytics, Text Analytics, Web Analytics, Data Integrity, Data Privacy and Security, Data Warehouse, Information Integration, Human Behavior Understanding, Data Mining, Semi-Structured and Unstructured Data, Data Fusion, Pattern Recognition, Predictive Modelling, Data Mining, Statistical and Structural Pattern Recognition, Performance Analysis and Evaluation, Evolutionary Computing and Optimization, Feature Selection, Fuzzy Computing, Hybrid Methods, Neural Networks, Deep Learning, Process Mining, Granular Computing, Mobile data, City Data Management, Transparency in Research Data, Data and Information Quality, Data Virtualization, Management of Sensor Data, Semantic Web Technologies, Big Data"