| Data Mining and Data Quality
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Theme:
Data Mining is a vibrant discipline that covers feature extraction from the structured and unstructured data sources. Academic studies and industry experience have shown that poor data quality can have an adverse impact not only on data mining but on all types of information processes. However, what is not clearly understood is the degree to which types (dimensions) of data quality defects in source data have an impact on the results of a particular information process. The theme of this track is to solicit and stimulate research in both data mining and data quality and to explore the relationships between data quality to data mining .
Topics:
- Data quality and data mining
- Data quality and machine learning
- Data quality and master data management
- Data quality in healthcare data
- Data quality in financial data
- Data quality standards and policies for data governance
- The detection and removal of bias in model training data
- Automatic generation of data quality validation rules
- Unsupervised methods to detect and correct data quality problems
- The application of data mining techniques to assess and improve data quality
- The application of data mining techniques in privacy preservation
- Data mining systems
- Data mining languages
- Data mining methodologies
- Interactive data mining
- Big Data
- Mining knowledge in multidimensional spaces
- Online Analytical Processing
- Text Mining
- Web Mining
- Social media mining
Paper Submission:
Papers must represent high quality and previously unpublished
work, not currently under review by another conference,
workshop, or journal. Interested authors
should upload a 6-page version of their original and unpublished
work including 5 keywords to ITNG 2024 via submission link below. Initial submissions must remove author names, affiliations, and any other self-identifying information for coding and blind review purposes. Author information will be added in the final submission of accepted papers.
https://easychair.org/my/conference?conf=itng2024
Evaluation Process:.
Papers will be evaluated for originality, significance, clarity, and soundness.
Per ITNG policy, except for invited papers, all papers will be reviewed by at
least two independent reviewers.
Best Student Paper:
The Best Student Paper will be awarded at the conference. To be eligible,
the student must be the sole author of the paper, or the first author and primary
contributor. (The winner of the award will present the paper in a plenary session
at the conference). A cover letter to the General Chair/Track Chair must identify
the paper as a candidate for this competition at the time of submission.
IMPORTANT_NOTICE
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