Contains the code for my SEC11 original research project, a Wikipedia article recommender system using network structure for recommendations.
To use, get the dependencies (numpy/scipy, tqdm) and download the wiki-topcats dataset from SNAP.
For the input I recommend writing a file with the inputs and using cat fname.input - | python set_similarity.py
so the program doesn't get fed EOF at the end of the file. Then you can keep playing with more inputs. Alternatively just pickle a subgraph instead of building a random one each time and it should run pretty quick.
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Network-Based Content Recommendation for Wikipedia Articles
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