
The DBLP co-authorship network is a hypergraph where nodes are authors from the DBLP computer science bibliography database and hyperedges are papers, representing sets of authors who collaborated on a publication. Each author is labeled with their primary research area, inferred from the majority research area of their publications. The research areas include Database, Data Mining, AI, Information Retrieval, Computer Vision, and Machine Learning. This dataset is commonly used as a benchmark in hypergraph learning tasks for author classification and link prediction. Find the dataset details in AHORN.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
