{"title":"本体驱动的用户配置文件挖掘的个性化模型","authors":"Cuncun Wei, Chong-ben Huang, HengSong Tan","doi":"10.1109/IUCE.2009.128","DOIUrl":null,"url":null,"abstract":"User modeling is a key technology in implementing personalized services. This paper tried to solve disadvantage of lack of semantic information of keyword, and designed a user profiles modeling method based on the category knowledge base, combining the keywords and the ontology concepts. In the model the user profiles consist of short-term interest and long-term interest, and two different mechanisms of establishing and updating were adopted for these two kinds of interest. At last, the effectiveness of the method is verified through the experiment. It shows that this model can accurately reflect the characteristics of the user’s interest and improve the efficiency of information retrieval.","PeriodicalId":153560,"journal":{"name":"2009 International Symposium on Intelligent Ubiquitous Computing and Education","volume":"18 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"A Personalized Model for Ontology-driven User Profiles Mining\",\"authors\":\"Cuncun Wei, Chong-ben Huang, HengSong Tan\",\"doi\":\"10.1109/IUCE.2009.128\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"User modeling is a key technology in implementing personalized services. This paper tried to solve disadvantage of lack of semantic information of keyword, and designed a user profiles modeling method based on the category knowledge base, combining the keywords and the ontology concepts. In the model the user profiles consist of short-term interest and long-term interest, and two different mechanisms of establishing and updating were adopted for these two kinds of interest. At last, the effectiveness of the method is verified through the experiment. It shows that this model can accurately reflect the characteristics of the user’s interest and improve the efficiency of information retrieval.\",\"PeriodicalId\":153560,\"journal\":{\"name\":\"2009 International Symposium on Intelligent Ubiquitous Computing and Education\",\"volume\":\"18 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Symposium on Intelligent Ubiquitous Computing and Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IUCE.2009.128\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Symposium on Intelligent Ubiquitous Computing and Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IUCE.2009.128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Personalized Model for Ontology-driven User Profiles Mining
User modeling is a key technology in implementing personalized services. This paper tried to solve disadvantage of lack of semantic information of keyword, and designed a user profiles modeling method based on the category knowledge base, combining the keywords and the ontology concepts. In the model the user profiles consist of short-term interest and long-term interest, and two different mechanisms of establishing and updating were adopted for these two kinds of interest. At last, the effectiveness of the method is verified through the experiment. It shows that this model can accurately reflect the characteristics of the user’s interest and improve the efficiency of information retrieval.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
