Ismam Hussain Khan, Md Habib Ullah Khan, M. K. Howlader
{"title":"一种基于机器学习的食品配方评级预测智能方法","authors":"Ismam Hussain Khan, Md Habib Ullah Khan, M. K. Howlader","doi":"10.1109/CAIDA51941.2021.9425031","DOIUrl":null,"url":null,"abstract":"In recent times, there are many studies and systems which deal with restaurant rating or individual food rating but rating a recipe using Artificial Intelligence is rare. This study aims to rate recipes based on different attributes using different Machine Learning algorithms. It compares the performance of different classifiers in rating a recipe based on different performance criterion. This can be economically beneficial to restaurants by helping them improve their recipes and getting more customers. It can also be used in a more personal level to improve household recipes and for the customers of restaurants to decide which restaurant is better for a specific dish based on how good their recipe is.","PeriodicalId":272573,"journal":{"name":"2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Intelligent Approach for Food Recipe Rating Prediction Using Machine Learning\",\"authors\":\"Ismam Hussain Khan, Md Habib Ullah Khan, M. K. Howlader\",\"doi\":\"10.1109/CAIDA51941.2021.9425031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent times, there are many studies and systems which deal with restaurant rating or individual food rating but rating a recipe using Artificial Intelligence is rare. This study aims to rate recipes based on different attributes using different Machine Learning algorithms. It compares the performance of different classifiers in rating a recipe based on different performance criterion. This can be economically beneficial to restaurants by helping them improve their recipes and getting more customers. It can also be used in a more personal level to improve household recipes and for the customers of restaurants to decide which restaurant is better for a specific dish based on how good their recipe is.\",\"PeriodicalId\":272573,\"journal\":{\"name\":\"2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAIDA51941.2021.9425031\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAIDA51941.2021.9425031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Intelligent Approach for Food Recipe Rating Prediction Using Machine Learning
In recent times, there are many studies and systems which deal with restaurant rating or individual food rating but rating a recipe using Artificial Intelligence is rare. This study aims to rate recipes based on different attributes using different Machine Learning algorithms. It compares the performance of different classifiers in rating a recipe based on different performance criterion. This can be economically beneficial to restaurants by helping them improve their recipes and getting more customers. It can also be used in a more personal level to improve household recipes and for the customers of restaurants to decide which restaurant is better for a specific dish based on how good their recipe is.