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Experimenting with Wikipedia topics for Content
Automatically tagging your content with topics from a known, well described topic base like Wikipedia can have many cool uses. You can organize your content, suggesting keywords and outbound links, not to mention that you can build up interest profiles of your visitors. These interest profiles can the be used to suggest appropriate content and keep your visitors engaged. Inspired by Episerver Content Intelligence and a couple of earlier projects I've done in the past, I decided to perform an experiment to see how far I could get with a DIY approach as opposed to the traditional cloud-based NLP/AI.
Reading very large gzipped json files in c#
This is a little code snippet that I often find quite handy. It's a piece of c# code that opens a gzipped json file and iterates through the items in it. Since it takes it piece by piece (as opposed to loading everything in memory) it's can pretty much handle files of any size.
Showing the right block types at the right time
Often, it can be handy to have very exact and dynamic control over what editors can see or do. One of my weapons of choice for this is the good, old and trusted Virtual Roles. In this scenario we have a multi-site Episerver, where some of the block types it should only be possible to use on one of the sites.
Enrich Episerver Forms with additional system fields
Episerver forms adds a couple of system columns to each form submission when you export the submissions. But it happens that the people that need the form submission reports want additional data - for example the url of the page the form was on - and for some reason they don't know all Episerver page Guids by heart.