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Found 8 papers, 1 papers with code
Mapping job complexity and skills into wages
We use algorithmic and network-based tools to build and analyze the bipartite network connecting jobs with the skills they require.
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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The trickle down from environmental innovation to productive complexity
We study the empirical relationship between green technologies and industrial production at very fine-grained levels by employing Economic Complexity techniques.
A Bayesian approach to translators' reliability assessment
Translation Quality Assessment (TQA) is a process conducted by human translators and is widely used, both for estimating the performance of (increasingly used) Machine Translation, and for finding an agreement between translation providers and their customers.
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.
Universal Database for Economic Complexity
We present an integrated database suitable for the investigations of the Economic development of countries by using the Economic Fitness and Complexity framework.
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.
