A Rule-Based Expert Advisory System for Restaurants Using Machine Learning and Knowledge-Based Systems Techniques

IF 4.1 4区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

International Journal on Semantic Web and Information Systems Pub Date : 2023-11-07 DOI:10.4018/ijswis.333064

Khalid M. O. Nahar, Mustafa Banikhalaf, Firas Ibrahim, Mohammed Abual-Rub, Ammar Almomani, Brij B. Gupta

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引用次数: 0

Abstract

A healthy diet and daily physical activity are a cornerstone in preventing serious diseases and conditions such as heart disease, diabetes, high blood pressure, and hypertension. They also play an important role in the healthy growth and cognitive development for young and old people. Thus, this paper presents a new restaurant advisory system (RAS) using artificial intelligence (AI) techniques such as machine learning, decision tree, and rule-based methods. The proposed system makes a smart decision based on the user's input information to generate a list of appropriate meals that fit his/her health condition. For accuracy and efficiency measurement procedure in the decision-making process, a dataset from 1100 participants suffering from several diseases such as allergy, age, and body has been created and validated. The performance of the RAS was tested using Visual Basic.net Framework and prolog language. The RAS achieves an accuracy of 100% by testing 30 different live cases.

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使用机器学习和知识系统技术的基于规则的餐馆专家咨询系统

健康的饮食和日常身体活动是预防心脏病、糖尿病、高血压等严重疾病和病症的基石。它们在年轻人和老年人的健康成长和认知发展中也起着重要作用。因此，本文提出了一种新的餐厅咨询系统(RAS)，该系统使用人工智能(AI)技术，如机器学习、决策树和基于规则的方法。该系统根据用户的输入信息做出明智的决策，生成适合其健康状况的合适膳食列表。为了在决策过程中测量程序的准确性和效率，创建并验证了1100名患有过敏、年龄、身体等多种疾病的参与者的数据集。采用Visual Basic.net Framework和prolog语言对系统的性能进行了测试。RAS通过测试30个不同的活体病例，准确率达到100%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal on Semantic Web and Information Systems 工程技术-计算机：人工智能

CiteScore

6.20

自引率

12.50%

发文量

审稿时长

20 months

期刊介绍： The International Journal on Semantic Web and Information Systems (IJSWIS) promotes a knowledge transfer channel where academics, practitioners, and researchers can discuss, analyze, criticize, synthesize, communicate, elaborate, and simplify the more-than-promising technology of the semantic Web in the context of information systems. The journal aims to establish value-adding knowledge transfer and personal development channels in three distinctive areas: academia, industry, and government.