{"title":"Personalities Mining of Community Users Based on the Ontology Semantic Analysis","authors":"Wei Yu, T. Xiong","doi":"10.1109/IBICA.2011.100","DOIUrl":null,"url":null,"abstract":"Community marketing,whose core of precision marketing, is pushingthe advertisement to the users who really need it.In this article, through building the feature model and interest model of users , we use ontology analysis and semantic mining to analyse behavior characteristics,statement and comments,concerned content etc,and finally dynamically build the real feature attribut and interest set of community users. In addition, we use reasoning under uncertainty to deduce users' feature and interest. Our experiment demonstrate that this method peformance good accuracy on users' feature attribute and interest set.","PeriodicalId":158080,"journal":{"name":"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IBICA.2011.100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Community marketing,whose core of precision marketing, is pushingthe advertisement to the users who really need it.In this article, through building the feature model and interest model of users , we use ontology analysis and semantic mining to analyse behavior characteristics,statement and comments,concerned content etc,and finally dynamically build the real feature attribut and interest set of community users. In addition, we use reasoning under uncertainty to deduce users' feature and interest. Our experiment demonstrate that this method peformance good accuracy on users' feature attribute and interest set.