AI-powered
podcast player
Listen to all your favourite podcasts with AI-powered features
Enhancing Search Relevance with Re-ranking Strategies
The chapter explores strategies for re-ranking search results to improve relevance, focusing on methods like document perplexity and heuristics. It discusses the use of cross encoders and list-wise re-rankers in natural language processing, including the challenges and effectiveness of models like GPT4. Additionally, the conversation touches on incorporating metadata, user features, and persona-based recommendation systems into search algorithms for better user experience and results.