CiteSeer - This is the citation network extracted from the CiteSeer digital library. Nodes are publications and the directed edges denote citations.

Dataset

This dataset was created by MeeCreeps

Contents

Dataset

This dataset was created by Inv.Alireza babazadeh zarei

Released under Apache 2.0

Contents

The CiteSeer dataset consists of 3312 scientific publications classified into one of six classes. The citation network consists of 4732 links. Each publication in the dataset is described by a 0/1-valued word vector indicating the absence/presence of the corresponding word from the dictionary. The dictionary consists of 3703 unique words. The README file in the dataset provides more details.

The dataset used in the paper is citation networks, including Cora, Citeseer, and Pubmed.

Dataset Information

Nodes

Edges

Features

3,327 9,104 3,703

Pre-processed as per the official codebase of https://arxiv.org/abs/2210.02016

  Citations

@article{ju2023multi, title={Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization}, author={Ju, Mingxuan and Zhao, Tong and Wen, Qianlong and Yu, Wenhao and Shah, Neil and Ye, Yanfang and Zhang, Chuxu}, booktitle={International Conference on Learning… See the full description on the dataset page: https://huggingface.co/datasets/SauravMaheshkar/pareto-citeseer.

1.Cora dataset is derived from a multi-group citation network

The dataset used in the paper is a collection of real-world benchmark datasets for node classification.

Citation Graphs

including two types

Dataset

This dataset was created by Manvanth GS

Contents

CORA, Citeseer, Pubmed, OGB arXiv

If the dataset is used in publications, please cite the following papers: @inproceedings{giles1998jcdl, author = {C. Lee Giles and Kurt D. Bollacker and Steve Lawrence}, title = {{CiteSeer}: An Automatic Citation Indexing System}, booktitle = {Proceedings of the 3rd {ACM} International Conference on Digital Libraries, June 23-26, 1998, Pittsburgh, PA, {USA}}, pages = {89--98}, year = {1998}, url = {http://doi.acm.org/10.1145/276675.276685}, doi = {10.1145/276675.276685}, timestamp = {Tue, 18 Sep 2012 09:46:17 +0200}, biburl = {http://dblp.uni-trier.de/rec/bib/conf/dl/GilesBL98}, bibsource = {dblp computer science bibliography, http://dblp.org} }

The CiteSeerX dataset contains bibliographic records of publications from various fields of research.

We perform the distillation from trained teachers with various number of GCN layers: 2, 4, 6, 8, 16, 32, and 64. Student_MustaD is our distilled student that has the same hidden feature dimension as the teacher. Note that MustaD consistently outperforms other KD methods while preserving the multi-hop feature aggregation of the deep teacher.

CiteXplore combines literature search with text mining tools for biology. Search results are cross referenced to EBI applications based on publication identifiers. Links to full text versions are provided where available. The underlying database is populated with data from Medline, Patents, C.B.A. and Citeseer. The site offers a quick search as well as an advanced search. Results of queries can be saved in formats compatible with commonly-used bibliographic management software and exported. We provide a Simple Object Access Protocol (SOAP) based service to retrieve data from the Citation database. Text mining is provided internally by Whatizit and externally by iHOP.

The dataset used in the paper is a collection of real-world datasets with varying heterophily degrees, including Cora, Citeseer, Pubmed, Actor, Chameleon, Squirrel, Penn94, Genius, and Ogbn-arxiv.

A professional, social network and publication database geared to researchers where the latest field specific publications can be read, publications with other specialists can be discussed, and collaboration with colleagues is facilitated. They provide researchers with access to around 40 million abstracts and tens of thousands of Full texts, uploaded by the authors themselves. Researchers can search through 7 of the largest databases simultaneously, such as PubMed, IEEE & CiteSeer.

Yager DD. Structure, development, and evolution of insect auditory systems. Microsc Res Tech. 1999;47(6):380-400. doi:10.1002/(SICI)1097-0029(19991215)47:63.0.CO;2-P. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.608.8703&rep=rep1&type=pdf