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Leveraging Linked Data Analysis for Semantic Recommender Systems

  • Andreas Thalhammer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7295)

Abstract

Traditional (Web) link analysis focuses on statistical analysis of links in order to identify “influencial” or “authorative” Web pages like it is done in PageRank, HITS and their variants [10]. Although these techniques are still considered as the backbone of many search engines, the analysis of usage data has gained high importance during recent years [12]. With the arrival of linked data (LD), in particular Linked Open Data (LOD), new information relating to what actually connects different vertices is available. This information can be leveraged in order to develop new techniques that efficiently combine linked data analysis with personalization for identifying not only relevant, but also diverse and even missing information.

Keywords

Recommender System Link Open Data Recommendation Approach Main Page Music Recommendation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Andreas Thalhammer
    • 1
  1. 1.STI InnsbruckUniversity of InnsbruckAustria

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