2018 7th International Workshops on Database and Data Mining (ICDDM 2018) will be held during June 27-29, 2018 in Chongqing, China, hosted by Chongqing University of Posts and Telecommunications. It's the workshop of ICIVC 2018 - 2018 3rd International Conference on Image, Vision and Computing.
由重庆邮电大学主办,四川电子学会以及IEEE联合支持,将于2018年6月27-29日在中国重庆联合举办为期3天的第二届数据库与数据挖掘国际会议,忱欢迎从事相关技术研究的专家、学者和专业技术人员踊跃投稿并参加大会。
In today's information society, we witness an explosive growth of the amount of information becoming available in electronic form and stored in large databases. . For example, many companies operate huge data warehouses collecting many different types of information about their customers. As the workshops of ICIVC conference, ICDDM is for presenting novel and fundamental advances in the fields of Database and Data Mining. It also serves to foster communication among researchers and practitioners working in a wide variety of scientific areas with a common interest in improving Database and Data Mining related techniques. Topics of interest for submission include, but are not limited to:
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
Big data analytic and High performance implementations of data mining algorithms
Mining in targeted application contexts
Mining high speed data streams
Abnormality and data detection
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
Data cleaning and noise reduction
Data integration, data transformation, information extraction and recognition
Quality assessment, interestingness analysis, and post-processing
Statistical foundations for robust and scalable data mining
Handling imbalanced data, incomplete data or imperfect knowledge system
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, logistic management and risk management
Telecommunications, network and systems management