Information Retrieval Models

Information retrieval models are methods used by search engines to find and rank relevant information from large datasets based on user queries. They analyze the content of documents and the user's search terms to determine how well each document matches the query. Different models, such as Boolean, vector space, or probabilistic models, use mathematical techniques to evaluate relevance and produce an ordered list of results. These models aim to efficiently connect users with the most useful and appropriate information, ensuring that search results are accurate and meaningful for the query context.