Symbolic learning system for natural language understanding.

number: 
1184
إنجليزية
department: 
Degree: 
Imprint: 
Computer Science
Author: 
Zeina Abdul Razzaq Al-Jassani
Supervisor: 
Dr. Moaid Abdul Razzaq Fadhil
Dr.Taha Saadon Bashaga
year: 
2005

Abstract:

The present work is an attempt of designing a symbolic based learning system for natural language understanding. The field selected to be the domain of application is the subject of data structure. The technique of learning used is Symbolic Learning which is a combination of two learning strategies Rote Learning and Learning by Instruction. Symbolic learning methods are being developed for aiding the construction of systems requiring extraction of information from natural language documents and subsequent natural language querying of the resulting database. The system consists of the following modules, Process Query (Information Source) input to the learning system represented by the query entered by the end user, The Learning Engine carries out the learning task and produce knowledge for the knowledge base, Performance Engine make sure that the knowledge produced is useful . Visual Prolog Version 5.1 was used for building the system and its interface which provides Visual Development Environment (VDE).