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Advantages
The model doesn't need any data about other users, since
the recommendations are specific to this user. This makes
it easier to scale to a large number of users.
The model can capture the specific interests of a user,
and can recommend niche items that very few other users
are interested in.
Disadvantages
Since the feature representation of the items are hand-engineered
to some extent, this technique requires a lot of domain knowledge. Therefore,
the model can only be as good as the hand-engineered features.
The model can only make recommendations based on existing interests of
the user. In other words, the model has limited ability to expand on the
users' existing interests.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-07-26 UTC."],[],[]]