Emerging Need for Disruption in the Next Trend of Artificial Intelligence-Controlled Transformation Using Knowledge Mining
Nirmla Sharma1, Sameera Iqbal Muhmmad Iqbal2
1Dr. Nirmla Sharma, Assistant Professor, Department of Computer Science, King Khalid University, Abha, Kingdom of Saudi Arabia.
2Sameera Iqbal Muhmmad Iqbal, Department of Computer Science, King Khalid University, Abha, Kingdom of Saudi Arabia.
Manuscript received on 14 October 2024 | First Revised Manuscript received on 23 October 2024 | Second Revised Manuscript received on 02 January 2025 | Manuscript Accepted on 15 February 2025 | Manuscript published on 28 February 2025 | PP: 26-32 | Volume-14 Issue-3, February 2025 | Retrieval Number: 100.1/ijeat.C456414030225 | DOI: 10.35940/ijeat.C4564.14030225
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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: Knowledge mining is an emerging type of artificial intelligence (AI) that uses a grouping of AI facilities to determine insightful thoughts over huge volumes of unstructured, semi-structured, and structured data, which enables industries to extremely recognise their data, search it, expose insights, and find associations and designs at scale. Although the initial trend in AI contained numerous slight applications, such as preparing a specific model based on a single statistical basis for a particular problem, knowledge mining is the next trend in Artificial Intelligence, producing a large quantity of data associations and designs. It has rapidly brought a significant part of digital transformation creativity, which modifies how groups brand a sense of real-world statistics. Through this survey, we have analysed the responses of more than two-thirds of respondents to a current Harvard Business Brush up Analytic Services survey, and 68% of respondents believe that knowledge mining is key to achieving their corporations’ considered objectives over the next 18 months. Then, the requirement for knowledge mining is rapidly increasing. Eighty per cent are using physical approaches to switch unstructured data, and those approaches will be rapidly overtaken by the development of statistics, possibly in circumstances where this data has delivered an excessive rate.
Keywords: Association, Artificial Intelligence, Controlled, Knowledge Mining, Unstructured Data.
Scope of the Article: Artificial Intelligence and Methods