|Number of watchers on Github||134|
|Number of open issues||3|
|Average time to merge a PR||about 2 hours|
|Open pull requests||1+|
|Closed pull requests||0+|
|Last commit||about 7 years ago|
|Repo Created||about 7 years ago|
|Repo Last Updated||over 2 years ago|
|Organization / Author||karpathy|
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|View open issues (3)|
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This page contains code for Research Lei: http://cs.stanford.edu/people/karpathy/researchlei/
Google Group: https://groups.google.com/forum/?fromgroups#!forum/research-lei
Feel free to contact me for questions, suggestions on Twitter: https://twitter.com/karpathy or via email: email@example.com
Clone this repository
git clone https://github.com/karpathy/researchlei.git
(Optional) Make sure you have ImageMagick installed on your system if you'd like to extract image thumbnails from downloaded papers. In Ubuntu, this is available as
sudo apt-get install imagemagick
(Optional) Install pdftotext. This is included by default in many Linux distributions. This tool is used to extract all the words from a paper and find the top 100. Later, this can be used for other fancy processing, such as topic models, tfidf similarity rankings, etc.
You will need Python, preferrably Python 2.7.
Obtain Microsoft Academic Search API APP ID key and place it into a file
appid.txt. Since App ID's are rate limited to 200 queries per minute, I would strongly encourage you to obtain your own key from Microsoft (the request involves a single email and they reply fast). However, if you'd only like to check it out first for a bit, fill out this form.
You start with an empty database in the beginning. To add a paper, run, for example:
python addpaper.py name building rome in a day. This gets the
addpaper.py script to search Microsoft Academic Search by name for a paper with a title that contains the query words building, rome, in, a, day. The script will then guide you through downloading its citations, reference, and the actual .pdf of the paper. (Sadly, you may find that Microsoft's Academic Search is sparser than Google Scholar, especially with more recent work :( I contacted them about this and they said they are working on an update to their index. Unfortunately, Google Scholar does not provide convenient API, makes scraping difficult, and does not provide information that is as complete.)
The main Python script
addpaper.py creates a JSON file that the
client/index.html renders for the UI. Open it to see your library (remember to refresh it too every time you run
addpaper.py)! Some browsers like Safari and Chrome will not (by default) allow you to do an AJAX call to read the local JSON file. This can be fixed by starting Chrome with a special flag (--allow-file-access-from-files). In Ubuntu, you can drag the Chrome icon to desktop, right click -> properties and append it to Command. Alternatively, just use Firefox!
python addpaper.py name building rome in a day
Q: Microsoft Academic Search is sparser than Google Scholar, especially on very recent work. Could you use Scholar instead?
A: No. Google Scholar does not provide API that allows you to easily download their structured data. It is possible to scrape the HTML manually, but they aggressively throttle your requests. Even if you could, they don't provide as much data. For example, they don't provide references, abstracts, etc. Or if there are more than a few authors on a paper, they simply write
... and refer you to a publisher's page for the paper. I wish Google Scholar was as cool as Microsoft Academic Search. However, I've written MAS about this issue and they told me that they are actively working to index more papers and that we should all stay tuned. Lets hope for the best.