{"title":"社会化网络中基于关键词的推荐系统","authors":"Sandra Elizabeth Salim, R. Jebakumar","doi":"10.1109/ICIICT.2015.7396081","DOIUrl":null,"url":null,"abstract":"Social networks form an important platform for information sharing and interaction among users. The content from social networks can be used to generate recommendations for users in order to help them to choose what they desire. There exist a lot of recommendation methods currently. In this paper, we propose a keyword based recommendation system (KBRS), where the user's preferences are indicated by keywords. Here, we use a user based collaborative filtering (UCF) algorithm to provide recommendations. In order to support a more efficient and scalable execution, KBRS is implemented in Hadoop, using Map Reduce paradigm.","PeriodicalId":135283,"journal":{"name":"International Confernce on Innovation Information in Computing Technologies","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"KBRS — Keyword based recommendation system in social networks\",\"authors\":\"Sandra Elizabeth Salim, R. Jebakumar\",\"doi\":\"10.1109/ICIICT.2015.7396081\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Social networks form an important platform for information sharing and interaction among users. The content from social networks can be used to generate recommendations for users in order to help them to choose what they desire. There exist a lot of recommendation methods currently. In this paper, we propose a keyword based recommendation system (KBRS), where the user's preferences are indicated by keywords. Here, we use a user based collaborative filtering (UCF) algorithm to provide recommendations. In order to support a more efficient and scalable execution, KBRS is implemented in Hadoop, using Map Reduce paradigm.\",\"PeriodicalId\":135283,\"journal\":{\"name\":\"International Confernce on Innovation Information in Computing Technologies\",\"volume\":\"54 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Confernce on Innovation Information in Computing Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIICT.2015.7396081\",\"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 Confernce on Innovation Information in Computing Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIICT.2015.7396081","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
KBRS — Keyword based recommendation system in social networks
Social networks form an important platform for information sharing and interaction among users. The content from social networks can be used to generate recommendations for users in order to help them to choose what they desire. There exist a lot of recommendation methods currently. In this paper, we propose a keyword based recommendation system (KBRS), where the user's preferences are indicated by keywords. Here, we use a user based collaborative filtering (UCF) algorithm to provide recommendations. In order to support a more efficient and scalable execution, KBRS is implemented in Hadoop, using Map Reduce paradigm.