An Emergence of AI in Data Mining and KDD: ANN its Strength & Weakness
Mohammad Asim khan1, Sharik Ahmad2
1Mohammad Asim khan, Research Scholar, Department of Computer Science and engineering Glocal University, Saharanpur, India.
2Sharik Ahmad, Department of Computer science and engineering, Glocal university, Saharanpur India.
Manuscript received on April 03, 2020. | Revised Manuscript received on April 14, 2020. | Manuscript published on May 30, 2020. | PP: 380-383 | Volume-9 Issue-1, May 2020. | Retrieval Number: A1462059120/2020©BEIESP | DOI: 10.35940/ijrte.A1462.059120
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Rapid increases in informational and technological methods have led companies to gather customer data in great databases. Data mining is the procedure involving analyzing, searching information to make it helpful for human use. Great amount of information is modeled, selected as well as explored in order to figure out comprehensible info. Artificial intelligence as well as data mining methods has been utilized in numerous domains to resolve classification, diagnosis, and association, segmentation, and prediction issues. This particular paper discuss about the Data mining as well as KDD procedure from an AI perspective. We talk about popular subjects in data mining as well as AI, which includes key AI suggestions which have been utilized in both data mining as well as KDD. The general goal of this particular paper is taking a perspective of different application and algorithms of AI in Data Mining. In this particular paper, we are going to take into consideration several historic contributions and talk about these various thoughts with an example to human intelligence. Additionally, an overall framework for the style of even more clever devices can we proposed.
Keywords: Artificial intelligence, Knowledge discovery, Neural network, Data Mining.
Scope of the Article: Data Mining