Abstract
Searching a database records and ranking the results based on multicriteria queries is central for many database applications used within organizations in finance, business, industrial and other fields. For Example, the process of ranking (scoring) has been used to make billions of financing decisions each year serving an industry worth hundreds of billion of dollars. To a lesser extent, ranking has also been used to process hundreds of millions of applications by U.S. Universities resulting in over 15 million college admissions in the year 2000 for a total revenue of over $250 billion. College admissions are expected to reach over 17 million by the year 2010 for total revenue of over $280 billion. In this paper, we will introduce fuzzy query and fuzzy aggregation as an alternative for ranking and predicting the risk for credit scoring and university admissions, which currently utilize an imprecise and subjective process. In addition we will introduce the BISC Decision Support System. The main key features of the BISC Decision Support System for the internet applications are 1) to use intelligently the vast amounts of important data in organizations in an optimum way as a decision support system and 2) To share intelligently and securely company’s data internally and with business partners and customers that can be process quickly by end users. The model consists of five major parts: the Fuzzy Search Engine (FSE), the Application Templates, the User Interface, the database and the Evolutionary Computing (EC).
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Nikravesh, M., Bensafi, S. (2005). Soft Computing for Perception-Based Decision Processing and Analysis: Web-Based BISC-DSS. In: Nikravesh, M., Zadeh, L.A., Kacprzyk, J. (eds) Soft Computing for Information Processing and Analysis. Studies in Fuzziness and Soft Computing, vol 164. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32365-1_4
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