Google Cloud Professional Machine Learning Engineer — Question 79

Your company manages an application that aggregates news articles from many different online sources and sends them to users. You need to build a recommendation model that will suggest articles to readers that are similar to the articles they are currently reading. Which approach should you use?

Answer options

• A. Create a collaborative filtering system that recommends articles to a user based on the user’s past behavior.
• B. Encode all articles into vectors using word2vec, and build a model that returns articles based on vector similarity.
• C. Build a logistic regression model for each user that predicts whether an article should be recommended to a user.
• D. Manually label a few hundred articles, and then train an SVM classifier based on the manually classified articles that categorizes additional articles into their respective categories.

Correct answer: B

Explanation

The correct answer is B because using word2vec to encode articles as vectors allows for a similarity-based recommendation system that effectively identifies articles similar to those being read. Option A focuses on user behavior rather than article content, while option C does not leverage the content similarities effectively, and option D relies on manual labeling, which is not scalable or efficient for this purpose.