Learn About SherlockNet: Using Machine Learning to Tag and Caption the British Library’s Flickr Collection

Note: The SherlockNet project was a finalist in the British Library Labs Competition 2016.
From the Digital Scholarship Blog:

This is an update on SherlockNet, our project to use machine learning and other computational techniques to dramatically increase the discoverability of the British Library’s Flickr images dataset.
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One thing that’s awesome about making the British Library dataset via Flickr, is that Flickr provide an amazing API for developers. The API exposes, among other functions, the image website’s search logic via tags as well as free text search using the image title and description, and the capability to sort by a number of factors including relevance and “interestingness”. We’ve been working on using the Flickr API, along with AngularJS and Node.js to build a wireframe site.
You can check it out here.
If you look at the demo or the British Library’s Flickr album, you’ll see that each image has a relatively sparse set of tags to query from. Thus, our next steps will be adding our own tags and captions to each image on Flickr. We will pre-pend these with a custom namespace to distinguish them from existing user-contributed and machine tags, and utilise them in queries to find better results.

Learn More, Read the Complete Blog Post
See Also:  BL Labs Awards (2016): Enter Before Midnight 5th September!
See Also:  Black Abolitionist Performances and their Presence in Britain (The Other Finalist in the BL Labs Competition 2016)

Filed under: Awards, Data Files, Libraries, News