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Changed verbiage of cold-start assumption. Signed off by: Ian Hanus ([email protected])
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docs/source/user_guide/privacy_estimation/privacy_recommender.rst

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@@ -43,7 +43,7 @@ While this assumption may seem strong, it mirrors realistic scenarios where adve
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access to such data through creation of false users and webscraping.
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This implementation makes the assumption that each type of recommender system uses the most-popular algorithm
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to solve the cold start problem. This means that the most popular items are recommended to users
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to solve the cold start problem. This means that the candidates that are most popular are recommended to users
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who have no previous history of interaction with the system.
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This tool currently supports membership inference attacks in the context of collaborative filtering models.

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