MoCS is a system to visualize topics from the DBLP database of research papers. A live version of this code is available, including a description of the algorithms implemented and demonstrations of the maps rendered by the system, and a research paper describing how the system works.
Allows creation of basemaps through lib/cli_interface.py
.
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Install the python dependencies listed in requirements.txt. Using pip:
pip install -r requirements.txt
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Install graphviz
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Download NLTK corpora by running
python -m nltk.downloader brown langid
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Rename
lib/mocs_configTEMPLATE.py
tolib/mocs_config.py
Edit this file if your graphviz binaries or nltk data are in a non-standard location, or if you want the document database to be stored in a non-SQLite database. If this file is not edited, the DBLP data will be stored in a SQLite database calledmocs.db
in the project root. -
Run
./build_dblp.sh
to create the database and load it with data downloaded from DBLP.
Example Usage:
python lib/cli_interface.py perlis.pdf --author "%Perlis" --ending_year 1990
For a full list of command options:
python lib/cli_interface.py -h
Allows creation of basemaps and heatmaps.
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Install rabbitmq.
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Set up Django settings (optional). Edit
DATABASES
,SECRET_KEY
, andADMINS
insettings.py
, or create a new filelocal_settings.py
containing these parameters. If DATABASES is not edited, the Django tables will be stored in a SQLite database calledmocs.db
in the project root (which is by default the same database the DBLP data is stored in). -
Create Django databases:
./manage.py syncdb
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Run the server:
./manage.py celeryd ./manage.py runserver
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Access the map interface at
http://localhost:8000/maps/query/
Code is released under the MIT License.