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I have a set of a few thousand organisations (org) with some attributes (name, location, and type) and I want to identify the official URL for each organisation from a set of 10 URLs retrieved from Google.

The features to characterise org/URL pairs may include a few different string-matching scores, URL length, top-level domain, etc. Given the project constraints, I can generate a training/test set of correct pairs up to 100 or 150.

This can be seen as a binary classification problem between an organisation and a set of URL (true=official website). Another approach could be learning to rank, where the algorithm ranks the URLs and I pick the top one.

What algorithm/method would you recommend for this scenario, considering the small training set?

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