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DSML@DBAUG Publications Network
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Where does this come from?
The author names of the participants of the 1st DSML@DBAUG workshop were extracted, and google scholar was scraped to retrieve the most relevant results when their names were searched. Some of the participants did not have a google scholar account and there was a limit on the maximum number of possible requests on google-scholar. Nevertheless, 670+ publications were scraped. Also, no care was taken to filter out wrong hits on the author names (too much work). When you hover over a node the author name and the neighbors are highlighted.
And how was this concrete "author network" made?
This is how I did it:
  1. Google scholar web scraping (using a Selenium-based library called scholarly) was performed for the author names
  2. The first 20 results were kept (the results contain extended citation info - such as title, abstract, other authors, publication venue & year etc)
  3. The title and abstract were contatenated and a phrase embedding using a pre-trained transformer neural network were computed.
  4. A similarity between all the embeddings of the publications was then computed. This similarity is the edge weight between two nodes.
The visualization of the graph was adapted from this example
Credits
Web scraper Scholarly python library
Pre-trained transformer BERT