WebKB Cornell WebKB (GCN Benchmark)
A WebKB cornell dataset of 195 web pages, 286 hyperlinks, collected by Yang et al. (ICML 2016). Each record contains web page features, hyperlink edges, class labels. WebKB cornell university web page classification dataset. Suitable for node classification, web page categorization, graph neural networks.
Cite this dataset at
gcn-webkb-cornell.echo.directory
Analytics
Node size is centrality, colour is community. Hover a node for details; click one to isolate its community.
Computed over the full corpus.
Record
- Catalog key
gcn_webkb_cornell- Authors
- Craven, Mark; DiPasquo, Dan; Freitag, Dayne; McCallum, Andrew; Mitchell, Tom; Nigam, Kamal; Slattery, Seán
- Year
- 2000
- Source paper
- Learning to construct knowledge bases from the World Wide Web
- DOI / arXiv
- 10.1016/s0004-3702(00)00004-7
- License
- Academic Use (LicenseRef-Research-Only)
- Records
- 195
- Nodes
- 195
- Edges
- 286
- Nodes are
- web page
- Edges are
- hyperlink
- Attributes
- nodes have no attributes; edges have no attributes
- Languages
- en
- Collected
- 2016 (2010s)
- Tasks
- Node classification (multi-class;
label) inferred
From the graph: link prediction, community detection - Region
- Global (inferred: the platform is used worldwide)
Provenance
- Originally published at
- https://github.com/kimiyoung/planetoid link checked
- Hosted copy
- Mirrored on echo.directory on 2026-10-09, 18.9 MB across 80 files. Checksums in MANIFEST.json.
Citations
Learning to construct knowledge bases from the World Wide Web
M. Craven, Dan DiPasquo, Dayne Freitag, Andrew Mccallum, Tom Michael Mitchell
Journal Article · Artificial Intelligence · 2000
Cited by
- Semi-Supervised Learning
E. Martin, S. Kaski et al. · Encyclopedia of Database Systems · 2019 · cited 4.4K× - Open Information Extraction from the Web
Oren Etzioni, Michele Banko et al. · CACM · 2007 · cited 2.6K× - Predicting missing links via local information
Tao Zhou, Lin-Yuan Lu et al. · 2009 · cited 1.8K× - Snowball: extracting relations from large plain-text collections
Eugene Agichtein, L. Gravano · Digital library · 2000 · cited 1.5K× - Unsupervised named-entity extraction from the Web: An experimental study
Oren Etzioni, Michael J. Cafarella et al. · Artificial Intelligence · 2005 · cited 1.3K×
Show all 10
- A Survey on Multi-view Learning
Chang Xu, D. Tao et al. · arXiv.org · 2013 · cited 1.3K× - Semi-Supervised Learning
O. Chapelle, Bernhard Schlkopf et al. · 2006 · cited 1.2K× - Link mining: a survey
L. Getoor, Christopher P. Diehl · SKDD · 2005 · cited 1.1K× - Key-Value Memory Networks for Directly Reading Documents
Alexander H. Miller, Adam Fisch et al. · Conference on Empirical Methods in Natural Language Processing · 2016 · cited 1.1K× - Web-scale information extraction in knowitall: (preliminary results)
Oren Etzioni, Michael J. Cafarella et al. · The Web Conference · 2004 · cited 938×
Citation data from Semantic Scholar, retrieved 2026-10-22.
How to cite
BibTeX
@misc{echo2026,
title = {ECHO: Exploratory Compendium of Humanity Online},
author = {Switzer, Braden and Zafarani, Reza},
year = {2026},
url = {https://echo.directory},
note = {Syracuse University}
}
@article{Craven_2000,
title = {Learning to construct knowledge bases from the World Wide Web},
volume = {118},
issn = {0004-3702},
url = {http://dx.doi.org/10.1016/s0004-3702(00)00004-7},
doi = {10.1016/s0004-3702(00)00004-7},
number = {1-2},
journal = {Artificial Intelligence},
publisher = {Elsevier BV},
author = {Craven, Mark and DiPasquo, Dan and Freitag, Dayne and McCallum, Andrew and Mitchell, Tom and Nigam, Kamal and Slattery, Seán},
year = {2000},
month = Apr,
pages = {69–113}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
Craven, M., DiPasquo, D., Freitag, D., McCallum, A., Mitchell, T., Nigam, K., & Slattery, S. (2000). WebKB Cornell WebKB (GCN Benchmark) [Data set]. https://doi.org/10.1016/s0004-3702(00)00004-7
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
Craven, Mark, et al. WebKB Cornell WebKB (GCN Benchmark). 2000, doi.org/10.1016/s0004-3702(00)00004-7.