Dette er CodeArts blog. Vi deler thought-leadership og tekniske tips og tricks - men som regel på engelsk.
Using TwentyThree video service with Episerver
Videos and well executed webinars are key tools in achieving a higher engagement and conversion rate from your visitors and customers. TwentyThree is a powerful video hub and webinar service. I was lucky enough to get an account and access to their API and that escalated quickly into a prototype integration into Episerver.
Profile Manager v2 - KQL edition
We just launched a new version of the online tool Profile Manager - a tool that makes it easier for developers and content analysts to work with Episervers Profile Store. The new version lets you easily try out different KQL queries and build Filter Definitions with them.
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.
Powerslice: Identify unused blocks
Powerslice might have a few years on it's back, but it's still a great editorial tool, when you are working with large amounts of content and have access to Episerver Find. Here's an example of a recent slice I made that let's editors easily identify unused blocks.
Getting more Insight (pun intended) into Episerver Profile Store
Profile Store, Insight, Tracker, Advance - Episerver offers a myriad of different (but connected) REST services for managing and tracking your visitors and prospects. It can be slightly confusing at first - and some of the documentation might be a tad misleading - but once you get the hang of it, they are really powerful tools. I've recently had a chance to explore them in depth. Here is what I've learned so far.
Auto Tagging Using Search
You don't always have to go the full AI route to get AI like results. In this blog post I'll describe an approach I've used several times (and for multiple purposes) with pretty decent results. Instead of classification algorithms, deep learning or neural networks I'll just simply query my favorite search engine.
Storage Performance Aftermath - ElasticSearch Joins the Fight
In 3 previous blog posts I compared various azure storage technologies with regards to performance and scalability in typical web usage scenarios. I was actually done with the series, but with all that interesting data, I decided to throw my current favorite search/storage/no-sql technology into the mix to get an idea about how it all compares. So - ElasticSearch enters the competition!
Azure Storage Performance Showdown (Post 3)
This is the 3rd post in my Azure Storage Performance comparison. So far we've examined the typical scenario of storing/retrieving data that most dynamic websites of today deal with. In this post, we'll take a closer look at Update and Delete - and finally review the financial aspects.
Azure Storage Performance Showdown (Post 1)
Almost every project has some data you want to persist, then read, search through, update and eventually delete. With Azure there are loads of great possibilities - for example Blob Storage, Table Storage, CosmosDb, SQL Azure. I've decided to do some simple and fairly naive tests to compare these for some typical usage scenarios and see how they perform.