Data stream mining between classical and modern applications : a review
Other Title(s)
تنقيب البيانات المتدفقة بين التطبيقات القديمة و الحديثة : مقال مراجعة
Author
al-Abd al-Aziz, Ammar Zahir Yasin
Source
al-Tarbiyah wa-al-Ilm : Majallat ilmiyah lil-Buhuth al-Ilmiyah al-Asasiyah
Issue
Vol. 30, Issue 5 (31 May. 2021), pp.30-43, 14 p.
Publisher
University of Mosul College of Education for Pure Science
Publication Date
2021-05-31
Country of Publication
Iraq
No. of Pages
14
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
Data mining (DM) is an amazing developing with incredible chances to advantage institutions centre of main data of information accumulated of conduct their customer and expected customer.
DM identified data included in information which questions and summaries cannot viably discover.
DM is a straight way to examining data of periodic data records and summing up in useful information - information could be used in expand outputs, reduction costs, or both.
DM allows clients to verify data of various measurements or points, classify it, and sum up the connections recognized.
There are four types of DM: 1) Classification and regression, 2) Clustering, 3) Association Rule Mining, and 4) Outlier/Anomaly Detection.
Tending to the velocity part of Big Data (BD) has as of late pulled in a lot of revenue in the investigation local area because of its critical effect on information from pretty much every area of life like medical services, financial exchange, and interpersonal organizations, and so on.
A lot of paper works verified the velocity challenge via stream mining data.
The majority of streaming mining data articles centres around adjusting primary classifications of algorithms, methods and techniques of classic information to the modified information circumstance.
This research explores widely the latest literature of mining stream data field recognizes the essential ready nodes supporting variance founded methods.
This study not simply benefits examiner to make strong assessment subjects and separate gaps in the field yet moreover helps specialists for DM and BD application structure headway.
American Psychological Association (APA)
al-Abd al-Aziz, Ammar Zahir Yasin. 2021. Data stream mining between classical and modern applications : a review. al-Tarbiyah wa-al-Ilm : Majallat ilmiyah lil-Buhuth al-Ilmiyah al-Asasiyah،Vol. 30, no. 5, pp.30-43.
https://search.emarefa.net/detail/BIM-1302544
Modern Language Association (MLA)
al-Abd al-Aziz, Ammar Zahir Yasin. Data stream mining between classical and modern applications : a review. al-Tarbiyah wa-al-Ilm : Majallat ilmiyah lil-Buhuth al-Ilmiyah al-Asasiyah Vol. 30, no. 5 (2021), pp.30-43.
https://search.emarefa.net/detail/BIM-1302544
American Medical Association (AMA)
al-Abd al-Aziz, Ammar Zahir Yasin. Data stream mining between classical and modern applications : a review. al-Tarbiyah wa-al-Ilm : Majallat ilmiyah lil-Buhuth al-Ilmiyah al-Asasiyah. 2021. Vol. 30, no. 5, pp.30-43.
https://search.emarefa.net/detail/BIM-1302544
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 41-43
Record ID
BIM-1302544