Data Mining Methods and Obstacles: A Comprehensive Analysis
Clicks: 1
ID: 313154
2023
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
0.0
/100
1 views
0 readers
AI Quality Assessment
Not analyzed
Readership in this journal
Ranked #572 of 705 articles by views in Journal of Computing & Biomedical Informatics
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 705 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
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.
| Reference Key |
imported_1777059451_69ebc67b6d1af
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Sunila Fatima Ahmad, Asad Hussain, Muhammad Asgher Nadeem, Arsalan Malik, Zubair Mushtaq, Kashif Hassan Khan, Zahra Abbas |
| Journal | Journal of Computing & Biomedical Informatics |
| Year | 2023 |
| DOI |
DOI not found
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.