Digital Learnings in Sitecore & Cloud

In Part 1 of this series, I covered the background of relevance scoring in search and covered setup of Search Studio and Sitecore CDP & Personalise. In part two I will work through some example code that pulls these products together to show end to end search capability using the setup we covered in the last post. This demo code provides a command line "head" which utilises the Sitecore and Search Studio APIs to return personalised search results for the provided search terms of user. Overview The high level flow of the demo application is reasonably simple: Console.WriteLine("Getting search model for user " + email); var searchModel = await GetModelForUserAsync(email); Console.WriteLine("Search Model calculated: " + searchModel); Console.WriteLine("Getting search results"); var searchResults = await GetSearchResultsAsync(searchModel, term); if (!(searchResults is null)) ...

I had the opportunity recently to present at a Sitecore User Group session with Sameer Maggon , the founder of SearchStax. We've used SearchStax for many years to provide cloud hosted managed Solr Cloud for customers -- Sitecore even use SearchStax in their own Managed Cloud offering -- and the now have a new SaaS offering called Search Studio that lets you define different models to apply to searches which alter how relevance scoring is calculated. In part one of this blog post, I'll cover the main moving parts of SearchStax and Sitecore Personalise used to drive the solution. In part two I go through some example code that uses the two configured products together to render personalised search results. Relevance scoring When content is indexed for searching, the contents are tokeninsed and put into an index. Information is stored in a "Document" (either tokenised or stored directly) with term vectors associated. Term vectors are essentially the individ...