In information retrieval, relevance is a measure of how well retrieved content meets the user's information need. It encompasses factors like topical alignment, timeliness, authority, and novelty. High relevance ensures that search results (or AI-generated answers) accurately satisfy user queries in both context and content.
What are Evaluation Measures in Information Retrieval?
Evaluation measures in IR are metrics used to assess how effectively a system retrieves relevant content. Common measure...
What are Precision and Recall?
Precision measures the percentage of retrieved documents that are relevant to a query, while Recall measures the percent...
What is Ansehn?
Ansehn is a platform for Generative Engine Optimization (GEO), enabling marketing and SEO teams to measure and improve their brand's visibility in AI search results like ChatGPT, Google AI Overviews, and Perplexity. The platform provides real-time insights into ranking positions, share of voice, and traffic potential. Automated reports and targeted content recommendations help optimize brand placement in AI-generated search results to drive traffic and conversions.
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