bibcheck.py is a simple python class / command line utility for doing automated literature searches using Google Scholar. It takes as input a BibTeX bibliography (.bib) file and outputs a list of papers that might be relevant to the papers contained in the bibliography.
When used from the command line, the program returns a list of suggested papers, and the number of references each suggested paper has in common with the supplied bibliography.
The recommendations are generated by triangle closing. Briefly, we consider each paper in the bibliography as a node in a network, along with the bibliography itself. Edges connect the bibliography to each paper it cites. Each cited paper also has edges connecting it to other papers which include it in their bibliographies. To make recommendations, the code searches for other nodes, which when connected to the node of the supplied bibliography, would create multiple triangles in the network.
A more intuitive example: if you know Alice, Bob, Carol, and Dan, and Elise knows Bob, Carol, and Dan, then you are likely to know Elise. A hypothetical link between you and Elise would create three new triangles: (you, Bob, Elise), (you, Carol, Elise), and (you, Dan, Elise).
bibcheck.py is built on top of a couple great python libraries; thanks to @ckreibich for building scholar.py and to @sciunto for building python-bibtexparser.
usage: bibcheck.py [-h] [-o outfile] [-c cookie-file] [-r N] bibfile
Search Google Scholar for papers which share references with a supplied BibTeX
bibliography file.
positional arguments:
bibfile the BibTeX (.bib) file to be parsed
optional arguments:
-h, --help show this help message and exit
-o outfile save output to file
-c cookie-file use cookies stored in file
-r N, --rmax N specify max number of references per article
All the options should be self-explanatory, except for rmax which is used to
filter out review articles with hundreds / thousands of citations. Any article
in the supplied bibliography with more than rmax citations will be excluded
from the search.
#####If you run into
Trying to get cluster ID for article N/N
Error: failed to pull Google Scholar cluster IDs. Probably running into a captcha.
try supplying a cookie file. To generate a valid cookie:
- open Google Scholar in a browser
- do a search, and solve the captcha
- view your browser's cookies via your favorite method
- copy 'value' and 'expiration' from the 'GSP' cookie into the supplied notarobot.cookie file
#####If you run into
(any error that that originates in scholar.py)
make sure you're using the bibcheck branch of hinnefe2/scholar.py.