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ABSTRACT
The success of the Semantic Web depends on the availability of Web pages annotated with metadata. Free form metadata or tags, as used in social bookmarking and folksonomies, have become more and more popular and successful. Such tags are relevant keywords associated with or assigned to a piece of information (e.g., a Web page), describing the item and enabling keyword-based classification. In this paper we propose P-TAG, a method which automatically generates personalized tags for Web pages. Upon browsing a Web page, P-TAG produces keywords relevant both to its textual content, but also to the data residing on the surfer's Desktop, thus expressing a personalized viewpoint. Empirical evaluations with several algorithms pursuing this approach showed very promising results. We are therefore very confident that such a user oriented automatic tagging approach can provide large scale personalized metadata annotations as an important step towards realizing the Semantic Web.
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CITED BY 16
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Yang Song , Ziming Zhuang , Huajing Li , Qiankun Zhao , Jia Li , Wang-Chien Lee , C. Lee Giles, Real-time automatic tag recommendation, Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, July 20-24, 2008, Singapore, Singapore
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Shengliang Xu , Shenghua Bao , Ben Fei , Zhong Su , Yong Yu, Exploring folksonomy for personalized search, Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, July 20-24, 2008, Singapore, Singapore
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Sheila Kinsella , Adriana Budura , Gleb Skobeltsyn , Sebastian Michel , John G. Breslin , Karl Aberer, From Web 1.0 to Web 2.0 and back -: how did your grandma use to tag?, Proceeding of the 10th ACM workshop on Web information and data management, October 30-30, 2008, Napa Valley, California, USA
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Ziyu Guan , Jiajun Bu , Qiaozhu Mei , Chun Chen , Can Wang, Personalized tag recommendation using graph-based ranking on multi-type interrelated objects, Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, July 19-23, 2009, Boston, MA, USA
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