Interweaving public user profiles on the web

  • Authors:
  • Fabian Abel;Nicola Henze;Eelco Herder;Daniel Krause

  • Affiliations:
  • IVS – Semantic Web Group & L3S Research Center, Leibniz University Hannover, Germany;IVS – Semantic Web Group & L3S Research Center, Leibniz University Hannover, Germany;IVS – Semantic Web Group & L3S Research Center, Leibniz University Hannover, Germany;IVS – Semantic Web Group & L3S Research Center, Leibniz University Hannover, Germany

  • Venue:
  • UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

While browsing the Web, providing profile information in social networking services, or tagging pictures, users leave a plethora of traces In this paper, we analyze the nature of these traces We investigate how user data is distributed across different Web systems, and examine ways to aggregate user profile information Our analyses focus on both explicitly provided profile information (name, homepage, etc.) and activity data (tags assigned to bookmarks or images) The experiments reveal significant benefits of interweaving profile information: more complete profiles, advanced FOAF/vCard profile generation, disclosure of new facets about users, higher level of self-information induced by the profiles, and higher precision for predicting tag-based profiles to solve the cold start problem.