Redis Stack as a recommendation engine
Typically, we would retrieve documents based on their data, which means that we would resort to different indexing methods to perform a search, such as TEXT, TAG, or NUMERIC. However, to provide realistic recommendations, we can’t just rely on the content or taxonomy of the information stored in a database – we must also rely on other methods that take into account the popularity and feedback from users who may have rated that content. This leads to the introduction of another variable: the relevance of the results. As an example, if a certain item is rated to be top-quality and affordable, our database should return this item rather than other items that are inferior or more expensive and sort the results by relevance.
In addition to searches based on the relevance of the documents, another type of recommendation can be based on the appearance of an item, or other properties that are also intrinsic, such as a textual description...
