ML Anthology

First-Order Learning for Web Mining

Mark Craven, Seán Slattery, Kamal Nigam
ECML-PKDD 1998 pp. 250-255
doi:10.1007/BFB0026695 /ecmlpkdd/1998/craven1998ecml-firstorder/

Abstract

We present compelling evidence that the World Wide Web is a domain in which applications can benefit from using first-order learning methods, since the graph structure inherent in hypertext naturally lends itself to a relational representation. We demonstrate strong advantages for two applications — learning classifiers for Web pages, and learning rules to discover relations among pages.

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Cite

Text

Craven et al. "First-Order Learning for Web Mining." European Conference on Machine Learning, 1998. doi:10.1007/BFB0026695

Markdown

[Craven et al. "First-Order Learning for Web Mining." European Conference on Machine Learning, 1998.](https://mlanthology.org/ecmlpkdd/1998/craven1998ecml-firstorder/) doi:10.1007/BFB0026695

BibTeX

@inproceedings{craven1998ecml-firstorder,
  title     = {{First-Order Learning for Web Mining}},
  author    = {Craven, Mark and Slattery, Seán and Nigam, Kamal},
  booktitle = {European Conference on Machine Learning},
  year      = {1998},
  pages     = {250-255},
  doi       = {10.1007/BFB0026695},
  url       = {https://mlanthology.org/ecmlpkdd/1998/craven1998ecml-firstorder/}
}