Using extension theory to design a fast data processing model

With the advent of the Internet and WWW in the late 1990s, intelligent systems have found another application area. In the Internet-based system, how to search for the desired information in a short time is very important for the agent, search engine and data mining systems. Thus, we try to design an intelligent system with the characteristics of low complexity, quick convergence and low output error for both academia and industry. We use grey relational analysis to select more important input variables to establish a simplified fuzzy model. Then, we exploit the concepts of extension theory to adjust the fuzzy model during the parameter identification to expedite the tuning process. Finally, the proposed extension-based fuzzy model is applied to implementing an intelligent information retrieval system for the search engine to stress the model´s applicability