Big Data – BigData 2023 12th International Conference, Held as Part of the Services Conference Federation, SCF 2023, Honolulu, HI, USA, September 23–26, 2023, Proceedings /
Big Data – BigData 2023 12th International Conference, Held as Part of the Services Conference Federation, SCF 2023, Honolulu, HI, USA, September 23–26, 2023, Proceedings / [electronic resource] :
edited by Shunli Zhang, Bo Hu, Liang-Jie Zhang.
- 1st ed. 2023.
- XIV, 232 p. 63 illus., 42 illus. in color. online resource.
- Lecture Notes in Computer Science, 14203 1611-3349 ; .
- Lecture Notes in Computer Science, 14203 .
Research Track -- A Survey on Cross-domain Few-Shot Image Classification -- Exploring the Predictive Power of Correlation and Mutual Information in Attention Temporal Graph Convolutional Network for COVID-19 Forecasting -- IoT Lakehouse: A New Data Management Paradigm for AIoT -- HMGR: A Hybrid Model for Geolocation Recommendation -- Non-essential Perspective on Thinking Law of Data Protection and Utilization -- The Shifting Role of Government in Government Data Openness -- How do we talk and feel about COVID-19? Sentiment Analysis of Twitter Topics -- Lightweight Weight Update for Convolutional Neural Networks -- Bioinformatics-based Acquisition Of Alzheimer's Disease Hub Genes -- Application Track -- Enhanced Campus Information Query System based on ChatGPT Interface and Local Content Database -- Prediction of TrkB complex and antidepressant targets leveraging big data -- Does Trust Improve Commercial InsuranceParticipation Behavior? -- Research on Big Data Empowering Ecological Governance -- Research on Complex Financial Ecosystem Modeling and Traceability Analysis Based on Heterogeneous Graph Attention Networks -- Short Paper Track -- Accelerate SVM Training with OHD-SVM on GPU -- Construction of data security system.
This book constitutes the refereed proceedings of the 12th International Conference, BigData 2023, Held as Part of the Services Conference Federation, SCF 2023, Honolulu, HI, USA, during September 23–26, 2023. The 14 full papers presented together with 2 short papers were carefully reviewed and selected from 27 submissions. The conference focuses on research track and application track.
9783031447259
10.1007/978-3-031-44725-9 doi
Big data.
Computer engineering.
Computer networks .
Artificial intelligence.
Big Data.
Computer Engineering and Networks.
Artificial Intelligence.
QA76.9.B45
005.7
Research Track -- A Survey on Cross-domain Few-Shot Image Classification -- Exploring the Predictive Power of Correlation and Mutual Information in Attention Temporal Graph Convolutional Network for COVID-19 Forecasting -- IoT Lakehouse: A New Data Management Paradigm for AIoT -- HMGR: A Hybrid Model for Geolocation Recommendation -- Non-essential Perspective on Thinking Law of Data Protection and Utilization -- The Shifting Role of Government in Government Data Openness -- How do we talk and feel about COVID-19? Sentiment Analysis of Twitter Topics -- Lightweight Weight Update for Convolutional Neural Networks -- Bioinformatics-based Acquisition Of Alzheimer's Disease Hub Genes -- Application Track -- Enhanced Campus Information Query System based on ChatGPT Interface and Local Content Database -- Prediction of TrkB complex and antidepressant targets leveraging big data -- Does Trust Improve Commercial InsuranceParticipation Behavior? -- Research on Big Data Empowering Ecological Governance -- Research on Complex Financial Ecosystem Modeling and Traceability Analysis Based on Heterogeneous Graph Attention Networks -- Short Paper Track -- Accelerate SVM Training with OHD-SVM on GPU -- Construction of data security system.
This book constitutes the refereed proceedings of the 12th International Conference, BigData 2023, Held as Part of the Services Conference Federation, SCF 2023, Honolulu, HI, USA, during September 23–26, 2023. The 14 full papers presented together with 2 short papers were carefully reviewed and selected from 27 submissions. The conference focuses on research track and application track.
9783031447259
10.1007/978-3-031-44725-9 doi
Big data.
Computer engineering.
Computer networks .
Artificial intelligence.
Big Data.
Computer Engineering and Networks.
Artificial Intelligence.
QA76.9.B45
005.7