H. Papadakis, N. Michalakis, P. Fragopoulou, C. Panagiotakis, A. Malamos
{"title":"电影评分:移动设备上的个性化电影推荐","authors":"H. Papadakis, N. Michalakis, P. Fragopoulou, C. Panagiotakis, A. Malamos","doi":"10.1145/3139367.3139383","DOIUrl":null,"url":null,"abstract":"Recommender systems try to predict the preferences of users for specific items, based on an analysis of previous consumer behaviour. In this paper, we present Movie SCoRe, a mobile device application for personalized movie recommendation, based on a novel recommendation algorithm. This easy-to-use application allows users to effortlessly specify their preferences by rating already watched movies. The application, in turn, employs the aforementioned state-of-the-art algorithm in order to provide the user with accurate, personalized movie recommendations. In this paper, we describe the design, implementation and functionality of the mobile-based application as well as the basis of the underlying recommendation algorithm.","PeriodicalId":436862,"journal":{"name":"Proceedings of the 21st Pan-Hellenic Conference on Informatics","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Movie SCoRe: Personalized Movie Recommendation on Mobile Devices\",\"authors\":\"H. Papadakis, N. Michalakis, P. Fragopoulou, C. Panagiotakis, A. Malamos\",\"doi\":\"10.1145/3139367.3139383\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recommender systems try to predict the preferences of users for specific items, based on an analysis of previous consumer behaviour. In this paper, we present Movie SCoRe, a mobile device application for personalized movie recommendation, based on a novel recommendation algorithm. This easy-to-use application allows users to effortlessly specify their preferences by rating already watched movies. The application, in turn, employs the aforementioned state-of-the-art algorithm in order to provide the user with accurate, personalized movie recommendations. In this paper, we describe the design, implementation and functionality of the mobile-based application as well as the basis of the underlying recommendation algorithm.\",\"PeriodicalId\":436862,\"journal\":{\"name\":\"Proceedings of the 21st Pan-Hellenic Conference on Informatics\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 21st Pan-Hellenic Conference on Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3139367.3139383\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 21st Pan-Hellenic Conference on Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3139367.3139383","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Movie SCoRe: Personalized Movie Recommendation on Mobile Devices
Recommender systems try to predict the preferences of users for specific items, based on an analysis of previous consumer behaviour. In this paper, we present Movie SCoRe, a mobile device application for personalized movie recommendation, based on a novel recommendation algorithm. This easy-to-use application allows users to effortlessly specify their preferences by rating already watched movies. The application, in turn, employs the aforementioned state-of-the-art algorithm in order to provide the user with accurate, personalized movie recommendations. In this paper, we describe the design, implementation and functionality of the mobile-based application as well as the basis of the underlying recommendation algorithm.