Start to give better recommendations

Assignment Help Computer Engineering

Reference no: EM133694513

Question: Consider a recommendation system (e.g., Netflix). Suppose that there is a malicious user with 10,000 fake email addresses. The user creates 10,000 Netflix accounts, and each account has the same user characteristics (same age, gender, likes, and dislikes). However, each fake user provides contradictory movie reviews. For example, a given fake user may claim to like Romantic Comedy films, but it rates "50 First Dates" (a Romantic Comedy) 1 out of 5 stars, whereas it rates "The Joker" (an Action Thriller) 5 out of 5 stars. What effect might this have on the recommendation system? 1. The system may give consistently wrong recommendations to a real user with no usage history. 2. The system will not be affected. 3. The system may give consistently incorrect recommendations to a real user with a long, legitimate usage history. 4. The system may give wrong recommendations to a user for a short time, but as usage history builds it will start to give better recommendations.

Reference no: EM133694513

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