Stream automatically suggests Jobs, Categories, and People that may be relevant to the message. The behaviour and logic behind how these suggestions are made differs depending on the tag & the first part of the message.
Jobs
Job Tags are suggested as we gather a set of the most recently created 1,000 Jobs.
The 1,000 Job set is first filled with Jobs that the user is subscribed to (Marked as Important) and then filled with the most recent unsubscribed Jobs (i.e. I have Marked as Important 200 jobs, then the next 800 that are loaded are recently created Jobs with no relation to me).
Stream then cycles through each of the 1,000 Jobs to find a match in the message subject line, or if the job is matched in the first 10,000 characters of the message.
A maximum of 3 Jobs will be suggested.
Categories
Categories are suggested by cross referencing the category tags name with a message subject line, as well as the first 10,000 characters of the message body, to find a match.
Stream displays any relevant suggestions followed by all remaining tags listed alphabetically.
People
Stream suggests People tags by taking a known first and last name of people on your team and cross references this with the subject, and first 10,000 characters of the message body, to find a match.
Stream displays any relevant suggestions first, and then all users in the current team alphabetically.
Suggested Tags only use the Label Name of the tags, it does not use the meta data inside like the Auto tagging does.
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