Link Discovery: A Comprehensive Analysis

  • Authors:
  • Nicolai Erbs;Torsten Zesch;Iryna Gurevych

  • Affiliations:
  • -;-;-

  • Venue:
  • ICSC '11 Proceedings of the 2011 IEEE Fifth International Conference on Semantic Computing
  • Year:
  • 2011

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Abstract

We present a comprehensive analysis of link discovery approaches. We classify them with regard to the type of knowledge being used, and identify three commonly used sources of knowledge: The text of a document, the document title, and already existing links. We analyze the influence of the knowledge source as well as of the amount of training data used. Results show that the link-based approach performs best if the amount of training data is huge. In a more realistic setting with fewer training data, the text-based approach yields better results.