Score Boosting and Decay Functions in Qdrant - Business Logic in Vector Search

Learn how to implement score boosting and decay functions in Qdrant vector database to enhance search relevance with custom business logic. Discover how to address common search challenges such as prioritizing fresh data over stale content, boosting results based on geographical proximity, and applying custom relevance scoring to meet specific business requirements. Explore the score boosting feature introduced in Qdrant 1.14, which enables re-ranking of initial prefetch results using custom expressions and sophisticated decay functions. Master the implementation of relevance drop-offs for time-sensitive data, proximity-based scoring for location-aware searches, and custom business logic integration to fine-tune search results according to your application's unique needs.