Mohammed F. Alhamid, Majdi Rawashdeh, Abdulmotaleb El Saddik
{"title":"环境智能环境下多媒体的情境感知推荐","authors":"Mohammed F. Alhamid, Majdi Rawashdeh, Abdulmotaleb El Saddik","doi":"10.1109/ISM.2013.80","DOIUrl":null,"url":null,"abstract":"Given today's mobile and smart devices, and the ability to access different multimedia contents in real-time, it is difficult for users to find the right multimedia content from such a large number of choices. Users also consume diverse multimedia based on many contexts, with different personal preferences and settings. For these reasons, there is a need to reinforce recommendation process with context-adaptive information that can be used to select the right multimedia content and deliver the recommendations in preferred mechanisms. This paper proposes a framework to establish a bridge between the multimedia content, the user and joint preferences, contextual information including the physiological parameters, and the Ambient Intelligent (AmI) environment, using multi-modal recommendation interfaces.","PeriodicalId":6311,"journal":{"name":"2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)","volume":"1 1","pages":"409-414"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Towards Context-Aware Recommendations of Multimedia in an Ambient Intelligence Environment\",\"authors\":\"Mohammed F. Alhamid, Majdi Rawashdeh, Abdulmotaleb El Saddik\",\"doi\":\"10.1109/ISM.2013.80\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Given today's mobile and smart devices, and the ability to access different multimedia contents in real-time, it is difficult for users to find the right multimedia content from such a large number of choices. Users also consume diverse multimedia based on many contexts, with different personal preferences and settings. For these reasons, there is a need to reinforce recommendation process with context-adaptive information that can be used to select the right multimedia content and deliver the recommendations in preferred mechanisms. This paper proposes a framework to establish a bridge between the multimedia content, the user and joint preferences, contextual information including the physiological parameters, and the Ambient Intelligent (AmI) environment, using multi-modal recommendation interfaces.\",\"PeriodicalId\":6311,\"journal\":{\"name\":\"2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)\",\"volume\":\"1 1\",\"pages\":\"409-414\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISM.2013.80\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISM.2013.80","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards Context-Aware Recommendations of Multimedia in an Ambient Intelligence Environment
Given today's mobile and smart devices, and the ability to access different multimedia contents in real-time, it is difficult for users to find the right multimedia content from such a large number of choices. Users also consume diverse multimedia based on many contexts, with different personal preferences and settings. For these reasons, there is a need to reinforce recommendation process with context-adaptive information that can be used to select the right multimedia content and deliver the recommendations in preferred mechanisms. This paper proposes a framework to establish a bridge between the multimedia content, the user and joint preferences, contextual information including the physiological parameters, and the Ambient Intelligent (AmI) environment, using multi-modal recommendation interfaces.