Ranking Algorithms

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Ranking algorithms determine the order in which items should appear so that the most useful or relevant options are shown first. In a search engine, they take a user’s query and score each matching document based on how well it fits what the user is looking for. In recommendation systems or content feeds, the same idea is used to predict which items a user is most likely to engage with.

Older ranking methods relied on simple signals such as keyword matching or link structure, while modern systems often use machine learning to learn scoring patterns from example data. These models combine many signals into a single score that helps decide the final order of results. Performance is judged by how well the top results match what the user actually wants, using metrics that measure relevance at the highest-ranked positions.

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