Link Discovery: A Comprehensive Analysis (bibtex)
by Nicolai Erbs, Torsten Zesch and Iryna Gurevych
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.
Reference:
Link Discovery: A Comprehensive Analysis Nicolai Erbs, Torsten Zesch and Iryna Gurevych, In Proceedings of the 5th IEEE International Conference on Semantic Computing (IEEE-ICSC), 2011.
Bibtex Entry:
@inproceedings{Erbs2011b,
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.},
address = {Palo Alto, CA, USA},
author = {Erbs, Nicolai and Zesch, Torsten and Gurevych, Iryna},
booktitle = {Proceedings of the 5th IEEE International Conference on Semantic Computing (IEEE-ICSC)},
pages = {83--86},
title = {{Link Discovery: A Comprehensive Analysis}},
url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6061290},
year = {2011}
}