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Found 4 papers, 1 papers with code
Which products activate a product? An explainable machine learning approach
In this paper, we propose a procedure to statistically validate the importance of the products used in the feasibility assessment.
Sapling Similarity: a performing and interpretable memory-based tool for recommendation
Measuring the similarity between either users or items is the basis of memory-based collaborative filtering, a widely used method to build a recommender system with the purpose of proposing items to users.
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Machine learning to assess relatedness: the advantage of using firm-level data
In this work, we compare networks and machine learning algorithms trained not only on country-level data, but also on firms, that is something not much studied due to the low availability of firm-level data.
Product Progression: a machine learning approach to forecasting industrial upgrading
Economic complexity methods, and in particular relatedness measures, lack a systematic evaluation and comparison framework.
