TABLE OF CONTENTS Gamil Serag-Eldin, Souad Souafi-Bensafi, Jonathan K.Lee, Wai-Kit Chan, Masoud Nikravesh
BISC Program, Computer Sciences Division, EECS Department
University of California, Berkeley, CA 94720, USA
Email: nikravesh@cs.berkeley.edu
Most of the existing search systems (software) are modeled using crisp logic and queries. In this chapter, we introduce fuzzy querying and ranking as a flexible tool allowing approximation where the selected objects do not need to exactly match the decision criteria resembling natural human behavior. The model consists of five major modules: the Fuzzy Search Engine, Application Templates, the User Interface, the Database, and Evolutionary Computing. The system is de-signed in a generic form to accommodate more diverse applications and to be delivered as stand-alone software to academia and businesses.
Searching database records and ranking the results based on multicriteria queries is central for many database applications used within organizations in finance, business, industry and other fields. Most of the available systems (software) are modeled using crisp logic and queries, which results in rigid systems with imprecise and subjective processes and results. In this chapter we introduce fuzzy querying and ranking as a flexible tool allowing approximation where the selected objects do not need to exactly match the decision criteria resembling natural human behavior [Nikravesh (2001b)], [Nikravesh, Azvine (2002)], [Nikravesh (2003a)].
The model consists of five major modules: the Fuzzy Search Engine (FSE), Application Templates (AT), the User Interface (UI), the Database (DB) and Evolutionary Computing (EC). We developed the software with many essential features. It is built as...
