Date of Award


Degree Name

Master of Science


Computer Science

First Advisor

Rahimi, Shahram


Most search applications in use today employ a keyword based search mechanism, which do not have any deductive abilities and are therefore unable to understand human perceptions underlying any given search. This paper proposes a framework for a Fuzzy Expert System for question-answer support while searching within a specific domain. Development of such a framework requires computing theories which can understand and manipulate the knowledge inherent in natural language based documents. To this end, we can now employ the newly introduced theory of Computing with Words (CW). The recent introduction of CW, by Lofti Zadeh, signifies a break from the traditional computing model and promises to enable analysis of natural language based information. In order to provide a bridge between raw natural language text and CW, the use of Probabilistic Context Free Grammar (PCFG) is proposed. Together the two theories form the core of the proposed framework that allows search applications to be constructed with the capabilities of deduction and perception analysis using a natural language interface.




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