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. © 2011 IEEE.
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CITATION STYLE
Erbs, N., Zesch, T., & Gurevych, I. (2011). Link discovery: A comprehensive analysis. In Proceedings - 5th IEEE International Conference on Semantic Computing, ICSC 2011 (pp. 83–86). IEEE Computer Society. https://doi.org/10.1109/ICSC.2011.63
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