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International Conference on Knowledge Discovery and Data Mining ICKDDM on April 22-23, 2024 in Boston, United States
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- Short Name: ICKDDM
- Event Type: Conference
- Presentation: Digital
- Website URL: https://waset.org/knowledge-discovery-and-data-mining-conference-in-april-2024-in-boston
- Program URL: https://waset.org/conferences-in-april-2024-in-boston/program
- Contact URL: https://waset.org
- Location: Boston, United States
- Date: April 22-23, 2024
- Final Submission: March 24, 2024
- Notification: April 15, 2024
- Organization: World Academy of Science, Engineering and Technology
- Conference Tags: data collection data integration data analytics big data machine learning intelligent systems data mining artificial intelligence metadata data management knowledge discovery data processing data warehousing text mining data engineering data visualization machine intelligence big data analysis data analysis database information retrieval security privacy databases information systems
Data mining foundations
Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis)
Algorithms for new, structured, data types, such as arising in chemistry, biology, environment, and other scientific domains
Developing a unifying theory of data mining
Mining sequences and sequential data
Mining spatial and temporal datasets
Mining textual and unstructured datasets
High performance implementations of data mining algorithms
Mining in targeted application contexts
Mining high speed data streams
Mining sensor data
Distributed data mining and mining multi-agent data
Mining in networked settings: web, social and computer networks, and online communities
Data mining in electronic commerce, such as recommendation, sponsored web search, advertising, and marketing tasks
Methodological aspects and the KDD process
Data pre-processing, data reduction, feature selection, and feature transformation
Quality assessment, interestingness analysis, and post-processing
Statistical foundations for robust and scalable data mining
Handling imbalanced data
Automating the mining process and other process related issues
Dealing with cost sensitive data and loss models
Human-machine interaction and visual data mining
Security, privacy, and data integrity
Integrated KDD applications and systems
Bioinformatics, computational chemistry, geoinformatics, and other science & engineering disciplines
Computational finance, online trading, and analysis of markets
Intrusion detection, fraud prevention, and surveillance
Healthcare, epidemic modeling, and clinical research
Customer relationship management
Telecommunications, network and systems management
Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis)
Algorithms for new, structured, data types, such as arising in chemistry, biology, environment, and other scientific domains
Developing a unifying theory of data mining
Mining sequences and sequential data
Mining spatial and temporal datasets
Mining textual and unstructured datasets
High performance implementations of data mining algorithms
Mining in targeted application contexts
Mining high speed data streams
Mining sensor data
Distributed data mining and mining multi-agent data
Mining in networked settings: web, social and computer networks, and online communities
Data mining in electronic commerce, such as recommendation, sponsored web search, advertising, and marketing tasks
Methodological aspects and the KDD process
Data pre-processing, data reduction, feature selection, and feature transformation
Quality assessment, interestingness analysis, and post-processing
Statistical foundations for robust and scalable data mining
Handling imbalanced data
Automating the mining process and other process related issues
Dealing with cost sensitive data and loss models
Human-machine interaction and visual data mining
Security, privacy, and data integrity
Integrated KDD applications and systems
Bioinformatics, computational chemistry, geoinformatics, and other science & engineering disciplines
Computational finance, online trading, and analysis of markets
Intrusion detection, fraud prevention, and surveillance
Healthcare, epidemic modeling, and clinical research
Customer relationship management
Telecommunications, network and systems management
Name: World Academy of Science, Engineering and Technology
Website: https://waset.org/
Address: UAE
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