Extract guidance and actions from Climate Change documents using Machine Learning

The Goal We are in the design and planning phase of a new climate change impact planning software product (related to "UN Sustainable Development Goal 13: Take urgent action to combat climate change and its impacts") . The product will recommend a set of actions that ordinary citizens can take to avoid, mitigate, adapt, or rebuild from climate change disasters. Although there is a wealth of guidance information out there in PDFs or on websites, rather than go through those one by one, we want to see if machine learning NLP and NLU techniques (and others?) could be used to automatically extract that kind of guidance from a document. Your Contribution We would like you to explore ML techniques on a set of PDF and website content and produce some "climate change actions" via a model. This is exploratory and so we anticipate a few iterations where you produce some outputs, we examine those, and see how to structure the results into our proposed action structure. At the start of the project we will provide a set of PDF content, some suggested sentence structures/keyword examples, and a proposed action format (in JSON) for the model, and anything else you need.