This package consists of two python (2.7) scripts which take no arguments.
scrapy is the only dependency (maybe json too, I never remember if that's a
base package).
scrape_easychair.py will ask for your username and password, and then store
the metadata from the bidding page into a json file papers.json. I hard coded
the bidding page for WWW2016.
rank_papers.py is meant to be run twice.
The first time it runs, it will output a file interests.txt that has a list
of keywords ordered by popularity. Delete lines from that file for keywords you
are not interested in, and leave lines that you are interested in. Sorry, no
"indifferent" option!
The second time rank_papers.py runs, it will use your interests to create a
desirability metric, with 1.00 meaning all keywords were desirable, and -1.00
meaning all keywords were undesirable. It will then print paper details to
stdout in descending desirability order. Protip: page through this with less
in one window and make your bids in another window.
If you want to further prune your interests, you can safely run
rank_papers.py again after changing interests.txt and it will update
correctly. If you want to start over, delete interests.txt.
Other generated files:
papers.ngrams.json normalizes keywords to lowercase, adds bigrams of all
keywords 3+ words long and trigrams of all keywords 4+ words long, and includes
the interest metric for the most recent run of rank_papers.py in case you
want to use it programmatically someplace else.