{"title":"迈向全面的推荐社交分享:以推加拉","authors":"H. Madhyastha, Megha Maiya","doi":"10.1145/2535771.2535776","DOIUrl":null,"url":null,"abstract":"On today's online social networks, a user can discover only those recommendations that her friends put in the effort to share. Therefore, we present the PullRec framework for enabling users to pull recommendations from their friends. PullRec employs two measures to minimize the effort involved in sharing recommendations. First, to reduce the onus on users to express their recommendations, PullRec proactively logs all the entities about which a user may have an opinion and attempts to infer the user's opinions. Second, to ensure that users are not spammed with irrelevant queries, when a user queries for recommendations on a certain topic, PullRec notifies only those friends of the user who are likely to have relevant recommendations. PullRec is a step towards enabling a user to discover all recommendations that her friends are willing to share with her.","PeriodicalId":203847,"journal":{"name":"Proceedings of the Twelfth ACM Workshop on Hot Topics in Networks","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Towards comprehensive social sharing of recommendations: augmenting push with pull\",\"authors\":\"H. Madhyastha, Megha Maiya\",\"doi\":\"10.1145/2535771.2535776\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"On today's online social networks, a user can discover only those recommendations that her friends put in the effort to share. Therefore, we present the PullRec framework for enabling users to pull recommendations from their friends. PullRec employs two measures to minimize the effort involved in sharing recommendations. First, to reduce the onus on users to express their recommendations, PullRec proactively logs all the entities about which a user may have an opinion and attempts to infer the user's opinions. Second, to ensure that users are not spammed with irrelevant queries, when a user queries for recommendations on a certain topic, PullRec notifies only those friends of the user who are likely to have relevant recommendations. PullRec is a step towards enabling a user to discover all recommendations that her friends are willing to share with her.\",\"PeriodicalId\":203847,\"journal\":{\"name\":\"Proceedings of the Twelfth ACM Workshop on Hot Topics in Networks\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Twelfth ACM Workshop on Hot Topics in Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2535771.2535776\",\"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 Twelfth ACM Workshop on Hot Topics in Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2535771.2535776","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards comprehensive social sharing of recommendations: augmenting push with pull
On today's online social networks, a user can discover only those recommendations that her friends put in the effort to share. Therefore, we present the PullRec framework for enabling users to pull recommendations from their friends. PullRec employs two measures to minimize the effort involved in sharing recommendations. First, to reduce the onus on users to express their recommendations, PullRec proactively logs all the entities about which a user may have an opinion and attempts to infer the user's opinions. Second, to ensure that users are not spammed with irrelevant queries, when a user queries for recommendations on a certain topic, PullRec notifies only those friends of the user who are likely to have relevant recommendations. PullRec is a step towards enabling a user to discover all recommendations that her friends are willing to share with her.
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