الفهرس 
Semantic Computing Overview
Model DesignOnly 14 pages are availabe for public view
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Abstract
Human’s memory has very complicated structure with an enormous storage space of data. There are also different mechanisms for storing data as neurons in the brain. The computer scientists have done many trials to simulate human’s memory using different techniques. There are several categories and organizations of the human’s memory. One of them is the semantic memory, which is necessary for the use of language. Semantic memory has several classification models according to the psycholinguistic view.
A novel model of the connectionist semantic memory model according to the neural-fuzzy concept is proposed with design and implementation. The fuzzy system consists in common of set of IF-THEN rules. The proposed model is implemented using Fuzzy Inference System (FIS) as the building structure of the memory model. The proposed memory model structure has the general construction of any neural-fuzzy system. This means it consists of five layers as; two input/output layers, and three hidden layers. The system also can read stored items’ data from an external database to be able to expand it at any time. This helps enlarging the number of relation between these items and their corresponding attribute to result in a meaningful statement.
There is an implementation of a compatible, easy, and well-designed Graphical User Interface (GUI) as an application to the proposed model. It also facilitates the search procedures and makes it faster. Its idea depends on building question/answering bank to get answer(s) to the query formed. The user can simply form his/her question using several popup menus representing the input data. After that, the program reads this input data, and evaluates the corresponding output statement for the input question using FIS structure. Then the answer(s) is (are) displayed on this GUI screen. Single answer or multiple answers is (are) appeared according to the user choice. The simulation results were promising and encouraging.