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Intelligent Decision Support Systems (Idss): A New Paradigm

1283 words - 5 pages

“Decision making is concerned with evaluating and ranking possible alternatives of action” [9]. “It is a process that involves multiple steps depending on the number of viable options and scenarios” [1]. A person has to look into the pros and cons of each option and consider all the alternatives, decision maker also needs to be able to forecast the outcome of each option for the given situation and based on all these criteria can determine the best option suitable [5]. Nowadays technology is playing a vital role in helping humans take decisions in an effective way by processing the data, analyzing it and providing the alternatives to choose from. There are a lot of information systems that have emerged in the past few years which are also called “Decision support systems” (DSS), which help decision makers in identifying and solving problems by making right decisions utilizing the data and different models available[11].With the advent of emerging technologies such as Artificial Intelligence (AI) in the Information and Computing industry, have given rise to a new form of DSS called as “Intelligent Decision Support Systems (IDSS)” , that can in some way imitate human cognitive abilities in decision making [10]. “An IDSS is a decision support system that makes extensive use of the intelligence exhibited by machines or software. Ideally, an intelligent decision support system should behave like a human consultant supporting decision makers by providing full control of”: 1) acquiring data 2) evaluating the data and 3) making the final decision [6].The aim of intelligent decision support system is therefore to emulate human decision-making capabilities as closely as possible.
Traditional Decision Support Systems:
The current literature shows that in the late 1960s the researchers mainly focused on developing the Model-driven DSS [12], and lot of papers were published in different computing journals by 1970 about the systems supporting better decisions [14,15].The next decade i.e. in the early and mid-1980’s a variety of financial planning systems, spreadsheet-based DSS and Group DSS have emerged [3].The DSS proposed so far were not sophisticated, they lack interoperability and visualization capabilities, and these limitations have led to the development of Data-driven DSS such as Data warehouses, Executive Information Systems, OLAP and Business Intelligence systems in the late 1980s and early 1990s[12].By analyzing the large amount of historical data the Data-driven DSS is able to achieve the highest level of functionality and decision support[13]. Later, With the advent of World Wide Web, internet and other computing technologies in the mid 1990’s, have made it possible to offer the DSS as a service and this led to the rise of Knowledge Driven DSS and Web-based DSS [2].”The field of computerized decision support is continuing to expand with the use of new technologies and creation of new applications” [12].

Traditional decision-making...

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