Board games recommender engine
Board game recommendation engine. View the recommendations live at Recommend.Games! Install via
pip install board-game-recommender
Training new recommender models
python3 -m pip install --upgrade pipenv pipenv install --dev pipenv shell
In order to train the models you will need appropriate game and rating data. You can either scrape your own using the board-game-scraper project or take a look at the BoardGameGeek guild to obtain existing datasets.
We use the recommender implementation by Turi Create. Two recommender models are supported out of the box:
RankingFactorizationRecommender(default): Learns latent factors for each user and game, generally yielding very interesting recommendations.
ItemSimilarityRecommender: Ranks a game according to its similarity to other ratings by a user, often resulting in less interesting recommendations. However, this model is also able to find games similar to a given game.
Run the training
Run the training via the main script:
python -m board_game_recommender --help
E.g., train the default BGG mode like so:
python -m board_game_recommender \ --train \ --games-file bgg_GameItem.jl \ --ratings-file bgg_RatingItem.jl \ --model model/output/dir
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