Beyond the known: exploratory and diversity search with vector embeddings

In a world inundated with information, not every search journey begins with a specific destination in mind. We perfected known-item searches and personalized recommendations, but there exists a vast, often underappreciated realm where users embark on quests without a precise goal, driven by curiosity, uncertainty, or the desire for exploration.

This talk will dive deep into exploratory and diverse search paradigms. We’ll unravel the complexities behind these search modes, differentiate them from our traditional understanding of search and recommendation, and discuss innovative strategies to serve users in these scenarios better.

Kacper Łukawski

Qdrant

Kacper Łukawski is a Developer Advocate at Qdrant - an open-source neural search engine. His experience is mainly related to data engineering, machine learning, and software design. Recently, he’s been exploring the world of similarity learning and vector search.