A Neural Network is an advanced machine learning model, derived from models like decision trees, that is specifically utilized in systems designed to calculate the Information Gain score for documents.
The neural network model operates by taking as input the semantic vectors (embeddings) of documents. Crucially, it processes both documents the user has already viewed and new, unviewed documents. By analyzing these inputs, the model outputs an Information Gain score for each new document. This score quantifies the extent of new, meaningful information the document offers compared to the information already consumed by the user.
The output from the neural network is critical for search ranking and personalization, as documents are prioritized based on their information gain scores, aiming to display those most likely to provide the most novel and valuable content tailored to the user’s current knowledge gaps and needs.