{"title":"内容如何影响Web中的聚类特性","authors":"Christopher Thomas, A. Sheth","doi":"10.1109/WI.2007.93","DOIUrl":null,"url":null,"abstract":"In World Wide Web, contents of web documents play important roles in the evolution process because of their effects on linking preference. A majority of topological properties are content-related, and among them the clustering features are sensitive to contents of Web documents. In this paper, we first observe the impacts of content similarity on web links by introducing a metric called Linkage Probability. Then we investigate how contents influence the formation mechanism of the most basic cluster, triangle, with a metric named Triangularization Probability. Experimental results indicate that content similarity has a positive function in the process of cluster formation in theWeb. Theoretical analysis predicts the contents influence on the clustering features in the Web very well.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":"{\"title\":\"How Contents Influence Clustering Features in the Web\",\"authors\":\"Christopher Thomas, A. Sheth\",\"doi\":\"10.1109/WI.2007.93\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In World Wide Web, contents of web documents play important roles in the evolution process because of their effects on linking preference. A majority of topological properties are content-related, and among them the clustering features are sensitive to contents of Web documents. In this paper, we first observe the impacts of content similarity on web links by introducing a metric called Linkage Probability. Then we investigate how contents influence the formation mechanism of the most basic cluster, triangle, with a metric named Triangularization Probability. Experimental results indicate that content similarity has a positive function in the process of cluster formation in theWeb. Theoretical analysis predicts the contents influence on the clustering features in the Web very well.\",\"PeriodicalId\":192501,\"journal\":{\"name\":\"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)\",\"volume\":\"68 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WI.2007.93\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WI.2007.93","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
How Contents Influence Clustering Features in the Web
In World Wide Web, contents of web documents play important roles in the evolution process because of their effects on linking preference. A majority of topological properties are content-related, and among them the clustering features are sensitive to contents of Web documents. In this paper, we first observe the impacts of content similarity on web links by introducing a metric called Linkage Probability. Then we investigate how contents influence the formation mechanism of the most basic cluster, triangle, with a metric named Triangularization Probability. Experimental results indicate that content similarity has a positive function in the process of cluster formation in theWeb. Theoretical analysis predicts the contents influence on the clustering features in the Web very well.