{"title":"上下文感知推荐系统和服务的调查","authors":"Ebunoluwa Ashley-Dejo, S. Ngwira, T. Zuva","doi":"10.1109/CCCS.2015.7374144","DOIUrl":null,"url":null,"abstract":"The advancement of the Internet, mobile and wireless technologies have produced a rapid change of information in terms of volume and accessibility. The enormous volume of information can be devastating especially to mobile users exceeding human ability to differentiate information which is relevant and that which is irrelevant. For many yzears now, recommender system have become well-known, and have been studied in various domains such as e-learning, online shopping, tourism to help overcome information overload. Recommendations are produced based on users who have interests in a particular thing or item. This recommendation process was further enhanced by incorporating context such as time, weather, and location to make recommendations more accurate and efficient. However, these systems have introduced context-aware recommender systems. This paper presents a survey of Context-aware recommender systems, the background and algorithms of Context-aware Recommender System, and also discusses the open issues of context-aware recommender systems.","PeriodicalId":300052,"journal":{"name":"2015 International Conference on Computing, Communication and Security (ICCCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"A survey of Context-aware Recommender System and services\",\"authors\":\"Ebunoluwa Ashley-Dejo, S. Ngwira, T. Zuva\",\"doi\":\"10.1109/CCCS.2015.7374144\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The advancement of the Internet, mobile and wireless technologies have produced a rapid change of information in terms of volume and accessibility. The enormous volume of information can be devastating especially to mobile users exceeding human ability to differentiate information which is relevant and that which is irrelevant. For many yzears now, recommender system have become well-known, and have been studied in various domains such as e-learning, online shopping, tourism to help overcome information overload. Recommendations are produced based on users who have interests in a particular thing or item. This recommendation process was further enhanced by incorporating context such as time, weather, and location to make recommendations more accurate and efficient. However, these systems have introduced context-aware recommender systems. This paper presents a survey of Context-aware recommender systems, the background and algorithms of Context-aware Recommender System, and also discusses the open issues of context-aware recommender systems.\",\"PeriodicalId\":300052,\"journal\":{\"name\":\"2015 International Conference on Computing, Communication and Security (ICCCS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Computing, Communication and Security (ICCCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCCS.2015.7374144\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Computing, Communication and Security (ICCCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCCS.2015.7374144","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A survey of Context-aware Recommender System and services
The advancement of the Internet, mobile and wireless technologies have produced a rapid change of information in terms of volume and accessibility. The enormous volume of information can be devastating especially to mobile users exceeding human ability to differentiate information which is relevant and that which is irrelevant. For many yzears now, recommender system have become well-known, and have been studied in various domains such as e-learning, online shopping, tourism to help overcome information overload. Recommendations are produced based on users who have interests in a particular thing or item. This recommendation process was further enhanced by incorporating context such as time, weather, and location to make recommendations more accurate and efficient. However, these systems have introduced context-aware recommender systems. This paper presents a survey of Context-aware recommender systems, the background and algorithms of Context-aware Recommender System, and also discusses the open issues of context-aware recommender systems.