We have a knowledge base that we have created in Confluence that we have connected to a Jira Service Desk. How are the related articles that display selected? What determines relevancy? Is it a combination of KB article Title, Content, and Tags? If the results are weighted what determines the best matches?
There is a little AI that is used to help best determine the answer. Initially, it looks at the title, content on the article, and labels. If you associated labels with specific request types this will also help. As individuals who are searching for answers mark the article as helpful or if the article is used to answer a question it will use the keywords in the search or the request to try and match the article in the future for specific keywords. So over time, it should get better at answering questions with more relevant articles. When starting out using keywords in the title and body of the KB is important as well as matching labels with request types. All this will help as you get started.
Hello everyone, Hope everyone is safe! A few months ago we posted an article sharing all the new articles and documentation that we, the AMER Jira Service Management team created. As mentioned ...
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