Anne presents first findings on applying machine learning to adaptation literature

The Applied Machine Learning Days are an annual conference where the focus is not just on the latest technical advances in computer science, but also on how this technology can best be used. This year, for the first time there was a track on climate change. Anne presented the first findings of his PhD project at the poster session of this track.

For this project, Anne used a Support Vector Machine to select abstracts that are relevant to climate change adaptation. This resulted in a dataset of nearly 45 thousand abstracts. He then further analysed this data using Topic Modelling (LDA), network clustering of co-citations, and geo-parsers. The result is a snapshot of a rapidly developing and diverse but also somewhat segmented and unequal field of studies.

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