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Contributions to Proceedings:

E. Michlmayr, S. Cayzer:
"Learning User Profiles from Tagging Data and Leveraging them for Personal(ized) Information Access";
in: "Proceedings of the Workshop on Tagging and Metadata for Social Information Organization, 16th International World Wide Web Conference (WWW2007)", Eigenverlag, 2007.



English abstract:
Due to the high popularity of social bookmarking systems, a large amount of metadata is available. Aggregating the metadata belonging to one user results in an user profile similar to those often used in Information Filtering. This paper shows how to create user profiles from tagging data. We present the \adatag{} algorithm for profile construction which takes account of the structural and temporal nature of tagging data. In addition, we explore ways of leveraging these user profiles. There are two main insights gained. Firstly, as we experienced in a small-scale user study, simply being able to view aggregated information about past tagging behavior was considered useful. Secondly, the user profile can be used to guide the user's navigation, that is, to provide the user with personalized access to information resources.

Keywords:
tagging user profiles dynamics information filtering visualisation hci


Electronic version of the publication:
http://publik.tuwien.ac.at/files/pub-inf_4595.pdf



Related Projects:
Project Head Gerti Kappel:
Wissenschafterinnenkolleg Internettechnologien


Created from the Publication Database of the Vienna University of Technology.