{"title":"社交机器人的个性化服装推荐","authors":"Leo Woiceshyn, Yuchi Wang, G. Nejat, B. Benhabib","doi":"10.1109/IRIS.2017.8250118","DOIUrl":null,"url":null,"abstract":"Social robots can assist individuals with performing a number of different daily tasks. One such task, which has not been extensively explored, is suggesting appropriate clothing to an individual. This paper presents a novel, autonomous, clothing recommendation system that employs social robots. The proposed system can autonomously recommend options, from a user's wardrobe, that are personalized to an activity at hand. The novelty of the system lies in its ability to learn from the individual users' preferences over time. The learning-based personalization feature allows the system to assist new users as well as adapt to users whose preferences change over time. Human-robot interaction studies were conducted to assess both the performance of the overall system as well as its potential long-term adaptability.","PeriodicalId":213724,"journal":{"name":"2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Personalized clothing recommendation by a social robot\",\"authors\":\"Leo Woiceshyn, Yuchi Wang, G. Nejat, B. Benhabib\",\"doi\":\"10.1109/IRIS.2017.8250118\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Social robots can assist individuals with performing a number of different daily tasks. One such task, which has not been extensively explored, is suggesting appropriate clothing to an individual. This paper presents a novel, autonomous, clothing recommendation system that employs social robots. The proposed system can autonomously recommend options, from a user's wardrobe, that are personalized to an activity at hand. The novelty of the system lies in its ability to learn from the individual users' preferences over time. The learning-based personalization feature allows the system to assist new users as well as adapt to users whose preferences change over time. Human-robot interaction studies were conducted to assess both the performance of the overall system as well as its potential long-term adaptability.\",\"PeriodicalId\":213724,\"journal\":{\"name\":\"2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IRIS.2017.8250118\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRIS.2017.8250118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Personalized clothing recommendation by a social robot
Social robots can assist individuals with performing a number of different daily tasks. One such task, which has not been extensively explored, is suggesting appropriate clothing to an individual. This paper presents a novel, autonomous, clothing recommendation system that employs social robots. The proposed system can autonomously recommend options, from a user's wardrobe, that are personalized to an activity at hand. The novelty of the system lies in its ability to learn from the individual users' preferences over time. The learning-based personalization feature allows the system to assist new users as well as adapt to users whose preferences change over time. Human-robot interaction studies were conducted to assess both the performance of the overall system as well as its potential long-term adaptability.