Survey on Integrating AI and Data Mining Functionalities into a Single System using DSS
Keywords:
Artificial Intelligence (AI), Data mining, Decision Support Systems (DSS), Explainable AI, Hybrid intelligent system, Machine learningAbstract
In this contemporary modality of dynamic information, companies are generating information in mammoth quantities each and every day. To be able to convert this raw data into something useful, we must be able to convert it to actionable items. Decision-makers increasingly use intelligent systems with information. The Decision Support Systems (DSS) have an extended history of assistance in complex decisions, however the traditional DSS tend to be a fixed program that is incapable of learning to cope with the dynamic scenario. The difference lies in the gap filled with the integration of Artificial Intelligence (AI) and Data Mining into a single DSS framework. AI brings in strong reasoning, forecasting, and automation as opposed to Data Mining which exposes the unclear patterns and trends. All of them, taken together, lead to more responsive, self-developing and foresighted decision support. The present paper is a review of the literature available on the fusion of such technologies in contemporary DSS. It discusses the lead integration models, methods, and patterns, which have been proposed in the new sources. Such use cases include such aspects as healthcare, finance, and supply chain management are mentioned. The review has been as data quality, scalability and user trust is critically commented helpful in guiding the future direction through the identification of open problems and future trends.
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