Review Schema
Markup for ratings and reviews, including who wrote them. It feeds the star ratings in search results, and gives an assistant something concrete to cite about your reputation.
Related terms
Unsupervised Learning
Training a model on unlabelled data and letting it find structure by itself — grouping similar customers, say, without being told what the groups are.
Search Intent
What somebody actually wants when they type a query: to learn, to compare, to buy, or to find a specific site. Matching it matters more than matching the words.
Explainability
How well a system can show why it reached a decision. It matters most where the decision affects somebody — a loan, a diagnosis, a job application — and “the model said so” is not an answer.
Fine-Tuning
Taking a general model and training it further on your own examples so it follows your tone or handles your particular task. Useful when prompting alone keeps producing nearly-right answers.
RAG (Retrieval-Augmented Generation)
A technique where the AI first searches a set of documents, then writes its answer from what it found. It is how assistants quote current information rather than whatever was in their training data.
Sentiment Analysis
Automatically judging whether text is positive, negative or neutral. Used to read reviews and messages at a scale nobody could read by hand.