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