Understanding Search Behavior

Every search professional needs data about users’ behavior. Data is fundamental for analyzing user behavior and improving search relevance, both with manual tuning and with machine learning. But until now, collecting user behavior data has been haphazard. Our open-source User Behavior Insights (UBI) system provides a client-side library for instrumenting webpages, a server-side library for collecting data, and analytical tools for understanding it. Critically, it defines a standard schema for behavior data so that the community can contribute additional analytical tools and have it integrated with personalization. With the emergence of even more ways of generating and ranking search results—neural dense search, neural sparse search, model fine-tuning, hybrid search, RAG—choosing the best mix of approaches for your search application becomes even more critical.

A joint presentation from Eric Pugh, CEO – OpenSource Connections & Stavros Macrakis, Senior Technical Product Manager for Open Search – AWS.

More informaiton about User Behaviour Insights in this Github project.