{"title":"基于模糊粗糙集的混合推荐本体","authors":"Hsun-Hui Huang, Horng-Chang Yang, E. H. Lu","doi":"10.1109/ICCE-TW.2015.7216942","DOIUrl":null,"url":null,"abstract":"In the paper, a novel ontology-based recommendation model based on a fuzzy-rough hybrid mechanism is proposed. This model integrates the principles of both content-based and collaborative filtering recommender systems. The proposed model unified user profile/item characteristics profile representations in a concept level space. Hence not only the user preferences and the correlation between items, but also the information of other users with similar preferences can be used for more precise recommendation.","PeriodicalId":340402,"journal":{"name":"2015 IEEE International Conference on Consumer Electronics - Taiwan","volume":"12 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A fuzzy-rough set based ontology for hybrid recommendation\",\"authors\":\"Hsun-Hui Huang, Horng-Chang Yang, E. H. Lu\",\"doi\":\"10.1109/ICCE-TW.2015.7216942\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the paper, a novel ontology-based recommendation model based on a fuzzy-rough hybrid mechanism is proposed. This model integrates the principles of both content-based and collaborative filtering recommender systems. The proposed model unified user profile/item characteristics profile representations in a concept level space. Hence not only the user preferences and the correlation between items, but also the information of other users with similar preferences can be used for more precise recommendation.\",\"PeriodicalId\":340402,\"journal\":{\"name\":\"2015 IEEE International Conference on Consumer Electronics - Taiwan\",\"volume\":\"12 5\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Conference on Consumer Electronics - Taiwan\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCE-TW.2015.7216942\",\"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 IEEE International Conference on Consumer Electronics - Taiwan","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCE-TW.2015.7216942","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A fuzzy-rough set based ontology for hybrid recommendation
In the paper, a novel ontology-based recommendation model based on a fuzzy-rough hybrid mechanism is proposed. This model integrates the principles of both content-based and collaborative filtering recommender systems. The proposed model unified user profile/item characteristics profile representations in a concept level space. Hence not only the user preferences and the correlation between items, but also the information of other users with similar preferences can be used for more precise recommendation.
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