Special Session 5: Data Mining and Query Processing

Data mining is the computational process of discovering patterns in relatively large data sets using approaches at the intersection of artificial intelligence, machine learning, statistics, and databases. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. According to the data and the purpose of mining, data mining can have different branches, which can be roughly divided into process mining, text mining, and predictive mining. In the process of data mining query processing, it is necessary to develop an advanced data mining query language, so that users can describe the relevant data sets, domain knowledge, data types to be mined, and the conditions and interest limits that must be met by the discovered patterns to describe the analysis task. specific data mining tasks. The query processing should be integrated with the database or data warehouse query language and be optimized for efficient and flexible data mining.

● Organizer:

Chair: Ling Wang, Northeast Electric Power University, China (smile2867ling@neepu.edu.cn)
Co-Chair: Xiaojun Luo, Liming Vocational University, China ( 20201028@lmu.edu.cn)
Co-Chair: Wei Ding, Shandong Computer Science Center (National Supercomputing Center in Jinan), Qilu University of Technology, China (dingw@sdas.org)

● Submission Method:

Please submit your manuscript to http://www.zmeeting.org/submission/hp3c2023 and select Track “Special Session 5: Data Mining and Query Processing”

● Papers for this session are based on various interests including but not limited to:
Social network;
process mining;
text mining;
predictive mining;
Spatial-temporal databases;
Geo-referenced objects query processing;
Moving objects model;