Expert System Shell Based On AIML And FAQ

Muchamad, Masduki Khamdan (2017) Expert System Shell Based On AIML And FAQ. Masters thesis, Universiti Teknikal Malaysia Melaka.

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Abstract

In the 2016, Forbes Magazine put McDonald's as the best fast food chains. The main factor of McDonald's achievements is the customers convenience. Currently, the system that is running in McDonald's generally less effective and lack of its time efficiency. Based on this problem the author aims to develop an intelligent system based on AIML interpreter, this application called as McBot intelligent system which is web based mobile application by transforming it into an intelligent waiter. There are three knowledge base to build the McBot intelligent base, which are Annotated A.L.I.C.E. AIML (AAA) files, Domain Specific Conversation and Frequently Asked Questions (FAQ). To implement this research, qualitative approach is used in this research. The evaluation of the McBot’s intelligence system is done by using black-box testing which is conducted using fifty datasets compiled from past competition questions of Loebner Prize Scored. The results of this testing was McBot was able to scored 72 points out of 100 points. Based on the result most of the questions are properly and correctly answered with total of 32 questions, 8 questions are partially met by the response and 10 questions are not met at all by the response. The results have shown that McBot has great potential being a conversation bot that can interact with end users. Even though the intelligent in this study is limited to only an general knowledge base and promotion, more information about the product can be added in the future. The contribution of this project is to build the McDonald’s expert system shell to adapt generic AIML and FAQ.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Expert systems (Computer science), System design, Systems engineering
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics > QA76 Computer software
Divisions:	Library > Tesis > FTMK
Depositing User:	Nor Aini Md. Jali
Date Deposited:	25 Apr 2018 09:23
Last Modified:	18 Feb 2022 15:11
URI:	http://eprints.utem.edu.my/id/eprint/20758
Statistic Details:	View Download Statistic

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