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Data Mining Methods and Obstacles: A Comprehensive Analysis
Institute of Information Technology, Quaid-e-Azam University, Islamabad, Pakistan.
Department of Computer Science, University of Science and Technology, Bannu, 28100, Pakistan.
Department of CS&IT, Thal University, Bhakkar, 30000, Pakistan.
Department of Computer Science, COMSATS University Islamabad, Pakistan.
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2023 (English)In: Journal of Computing and Biomedical Informatics, ISSN 2710-1606, Vol. 6, no 1, p. 394-406Article in journal (Refereed) Published
Abstract [en]

An in-depth analysis of the challenges and developments in the data mining industry is the aim of the study. To locate and assess relevant information on data mining approaches and difficulties, this study combines guided literature searches with real-world case studies. The research design includes information on the search terms, data sets, and selection standards for choosing which articles should be included and which should be omitted. Also, the study includes data extraction, outcomes interpretation, and paper quality assessment. The research focuses on data mining detection techniques and commercial challenges. The various data mining methods are discussed along with the challenges they face. Results from surveys, books, articles, published papers, finished projects, and reviews of earlier research are included in this analysis. According to the study's findings, data mining is a difficult occupation that is perpetually in need of advancement and creativity.

Place, publisher, year, edition, pages
Research Center of Computing and Biomedical Informatics , 2023. Vol. 6, no 1, p. 394-406
Keywords [en]
Data Analysis, Data Mining, Data Quality, Detection Methods, Obstacles
National Category
Other Civil Engineering
Identifiers
URN: urn:nbn:se:kth:diva-375819Scopus ID: 2-s2.0-105026792706OAI: oai:DiVA.org:kth-375819DiVA, id: diva2:2031998
Note

QC 20260126

Available from: 2026-01-26 Created: 2026-01-26 Last updated: 2026-01-26Bibliographically approved

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