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Feed Ranking Model

Feed Ranking Model

Learn about the Feed Ranking system architecture and the model requirements.

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3. Model

Feature engineering

Features Feature engineering Description
User profile: job title, industry, demographic, etc. For low cardinality: Use one hot encoding. Higher cardinality: use Embedding.
Connection strength between users Represented by the similarity between users. We can also use Embedding for users and measure the distance vector.
Age of activity Considered as a continuous feature or a binning value depending on the sensitivity of the Click target.
Activity features Type of activity,
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