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Found 5 papers, 3 papers with code
Dyport: Dynamic Importance-based Hypothesis Generation Benchmarking Technique
This paper presents a novel benchmarking framework Dyport for evaluating biomedical hypothesis generation systems.
Literature-based Discovery for Landscape Planning
This project demonstrates how medical corpus hypothesis generation, a knowledge discovery field of AI, can be used to derive new research angles for landscape and urban planners.
Towards Practical Explainability with Cluster Descriptors
The goal is to find a representative set of tags for each cluster, referred to as the cluster descriptors, with the constraint that these descriptors we find are pairwise disjoint, and the total size of all the descriptors is minimized.
Accelerating COVID-19 research with graph mining and transformer-based learning
In 2020, the White House released the, "Call to Action to the Tech Community on New Machine Readable COVID-19 Dataset," wherein artificial intelligence experts are asked to collect data and develop text mining techniques that can help the science community answer high-priority scientific questions related to COVID-19.
AGATHA: Automatic Graph-mining And Transformer based Hypothesis generation Approach
Hypothesis generation systems address this challenge by mining the wealth of publicly available scientific information to predict plausible research directions.
