Data Cleaning as a Prerequisite for Reliable Data Mining: An Analytical Study of Techniques, Challenges, and Performance Implications
Keywords:
Data mining, Data cleaning, Dirty dataAbstract
Data mining fundamentally involves the integration and synthesis of heterogeneous data sources, drawing upon methodologies from statistics, management science, and database systems to enable pattern recognition and knowledge discovery. As a result, data mining technology has experienced rapid advancement in contemporary society, accompanied by growing scholarly and professional interest in the convergence of data mining and data warehouse techniques. When data mining yields valuable insights, data warehouse technology plays a critical role in facilitating data integration. Within this framework, data cleaning is specifically concerned with the identification and rectification of erroneous or "dirty" data, which can compromise analytical validity. Consequently, robust data mining processes must incorporate data cleaning to ensure the authenticity and integrity of data stored in databases. In response to these requirements, China must continue to advance its research efforts in data mining and data cleaning, with a sustained focus on the development and refinement of effective strategies within this domain.
References
Ge, H., & Wu, Y. (2023). An Empirical Study of Adoption of ChatGPT for Bug Fixing among Professional Developers. Innovation & Technology Advances, 1(1), 21–29. https://doi.org/10.61187/ita.v1i1.19
Meng , L. (2023). Research on the Evaluation System of Green Cabling of Cables Based on Neural Network. Innovation & Technology Advances, 1(2), 25–31. https://doi.org/10.61187/ita.v1i2.37
Narouei, F. H., Tang, Z., Wang, S. I., Hashmi, R. H., Welch, D., Sethuraman, S., ... & McNeill, V. F. (2025). Effects of germicidal far-UVC on ozone and particulate matter in a conference room. Plos one, 20(8), e0328224.
Yang, J., Wang, Z., & Chen, C. (2024). GCN-MF: A graph convolutional network based on matrix factorization for recommendation. Innovation & Technology Advances, 2(1), 14–26. https://doi.org/10.61187/ita.v2i1.30
Xiao, J., Hai, L., Li, Y., Li, H., Gong, M., Wang, Z., ... & He, D. (2022). An Ultrasmall Fe3O4‐Decorated Polydopamine Hybrid Nanozyme Enables Continuous Conversion of Oxygen into Toxic Hydroxyl Radical via GSH‐Depleted Cascade Redox Reactions for Intensive Wound Disinfection. Small, 18(9), 2105465.
Song, X. (2025). User-Centric Internal Tools in E-commerce: Enhancing Operational Efficiency Through AI Integration.
Wu, W. (2025). Construction and optimization of intelligent gateway software management platform based on jenkins cluster management under cloud edge integration architecture in industrial internet of things. Preprints, January.
Chen, J. (2025). Design Optimization of Data Pipelines in Gig Economy Platforms: Improving Data Processing Efficiency.
Peng, Qucheng, Chen Bai, Guoxiang Zhang, Bo Xu, Xiaotong Liu, Xiaoyin Zheng, Chen Chen, and Cheng Lu. "NavigScene: Bridging Local Perception and Global Navigation for Beyond-Visual-Range Autonomous Driving." arXiv preprint arXiv:2507.05227 (2025).
PENG, Qucheng. MULTI-SOURCE AND SOURCE-PRIVATE CROSS-DOMAIN LEARNING FOR VISUAL RECOGNITION. 2022. PhD Thesis. Purdue University Graduate School.
Deng, X., Yang, Y., Wang, B., Zhang, X., Huang, S., Zhang, Y., & Lu, Q. (2026). LLM-MVR: LLM-Guided Multi-View Reasoning Distillation for Sarcasm Detection. Available at SSRN 6795979.
Junxi, Y., Wang, Z., & Chen, C. (2024). GCN-MF: A graph convolutional network based on matrix factorization for recommendation. Innovation & Technology Advances, 2(1), 14–26. https://doi.org/10.61187/ita.v2i1.30
Zhou, J., & Cen, W. (2024). Investigating the Effect of ChatGPT-like New Generation AI Technology on User Entrepreneurial Activities. Innovation & Technology Advances, 2(2), 1–20. https://doi.org/10.61187/ita.v2i2.124
Li, X., Yang, X., & Zhang, G. (2026, January). A Data-Driven Study on the Correlation between International Sales Strategies and Performance: An Empirical Model Based on the Theoretical Framework of International Trade. In Proceedings of the 2nd International Conference on Digital Society, Information Science and Risk Management (pp. 396-401).
Wang, Y., Jiang, K., Zhang, T., Tian, K., & Jiang, G. (2026). QA-ReID: Quality-Aware Query-Adaptive Convolution Leveraging Fused Global and Structural Cues for Clothes-Changing ReID. arXiv preprint arXiv:2601.19133.
Li, G., Yuan, H., Chen, S., Hu, Q., Wang, J., & Jiang, K. (2026). MFT: Memory-Aware Fine-Tuning of SAM2 for Efficient Long-Sequence Video Object Segmentation. IEEE Signal Processing Letters.
Zhou, Z. (2026). Hierarchical Needs in US Automotive Customer Feedback and the Sentiment–Function Nexus. Journal of Industrial Engineering and Applied Science, 4(1), 27-33.
Wensi, L. (2026). AI-Enabled Data Visualization Marketing for Automated Production Lines: Building Customer Trust and Improving Lead-to-Order Conversion. Academic Journal of Natural Science, 3(1), 8-13.
Shen, Zepeng, et al. "Research on Application of Whale Optimization Algorithm in Financial Payment Fraud Detection." 2025 4th International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID). IEEE, 2025.
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