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Colab examples

The GitHub repository hosts some IPython notebooks to get you start and running with the framework!

To use them you could use Google colab:

  • Go to Colab and open File > Open notebook

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  • Then go to GitHub section, write swapUniba/ClayRS in the first text box and choose the example you want to run!

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Available examples

All the following use the Movielens 100k dataset

  • 1_tfidf_centroid.ipynb: the easiest example, a good starting point for newcomers of the framework. It guides you in how to represent via TfIdf technique a field of the raw source, how to instantiate a CentroidVector algorithm and how to evaluate recommendations generated with several state-of-the-art metrics;

  • 2_embeddings_randomforest.ipynb: a slightly more complex example, where several fields are represented with several techniques, including embedding techniques. For the recommendation phase a Random Forest classifier is used;

  • 3_graph_pagerank.ipynb: it will guide you on how to perform graph based recommendation via ClayRS (how to instantiate a graph, how to manipulate it, how to load exogenous properties). The Personalized PageRank algorithm is used in the recsys phase;

  • 4_evaluate_other_recs.ipynb: a jolly example which shows how to export results (and intermediate results) obtained by ClayRS, but also how to evaluate external recommendation lists (i.e. recommendations generated via other tools)