V. Carchiolo, Marco Grassia, A. Longheu, M. Malgeri, G. Mangioni
{"title":"工地食堂食物推荐","authors":"V. Carchiolo, Marco Grassia, A. Longheu, M. Malgeri, G. Mangioni","doi":"10.5220/0010502401170124","DOIUrl":null,"url":null,"abstract":"Recommendation systems tackle with information overload to assist people in finding their best choice according to their preferences and past behaviour. This occurred in many contexts, including the food sector where culinary inspiration, sales increase or healthy advice motivate the adoption of such a system. In this paper we propose a canteen food recommendation system for workers operating at an innovation hub including more than 20 companies. The system leverages a 30 months data set of past choices, and adopts a content based and a collaborative filtering approach for canteen users, suggesting them with dishes chosen by other similar users. First results for frequent as well as occasional canteen visitors are encouraging to validate the proposed","PeriodicalId":414016,"journal":{"name":"International Conference on Complex Information Systems","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Food Recommendation in a Worksite Canteen\",\"authors\":\"V. Carchiolo, Marco Grassia, A. Longheu, M. Malgeri, G. Mangioni\",\"doi\":\"10.5220/0010502401170124\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recommendation systems tackle with information overload to assist people in finding their best choice according to their preferences and past behaviour. This occurred in many contexts, including the food sector where culinary inspiration, sales increase or healthy advice motivate the adoption of such a system. In this paper we propose a canteen food recommendation system for workers operating at an innovation hub including more than 20 companies. The system leverages a 30 months data set of past choices, and adopts a content based and a collaborative filtering approach for canteen users, suggesting them with dishes chosen by other similar users. First results for frequent as well as occasional canteen visitors are encouraging to validate the proposed\",\"PeriodicalId\":414016,\"journal\":{\"name\":\"International Conference on Complex Information Systems\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Complex Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0010502401170124\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Complex Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0010502401170124","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recommendation systems tackle with information overload to assist people in finding their best choice according to their preferences and past behaviour. This occurred in many contexts, including the food sector where culinary inspiration, sales increase or healthy advice motivate the adoption of such a system. In this paper we propose a canteen food recommendation system for workers operating at an innovation hub including more than 20 companies. The system leverages a 30 months data set of past choices, and adopts a content based and a collaborative filtering approach for canteen users, suggesting them with dishes chosen by other similar users. First results for frequent as well as occasional canteen visitors are encouraging to validate the proposed