Neural Search Improvements with Apache Solr 9.1 - Approximate Nearest Neighbor and Pre-Filtering
Overview
Explore the latest advancements in neural search technology with Apache Solr 9.1 in this informative 39-minute conference talk. Delve into the world of Artificial Intelligence-powered search engines that overcome vocabulary mismatch problems by learning term and sentence similarities through deep neural networks and numerical vector representations. Discover how these improvements allow for retrieval of relevant documents without requiring exact keyword matches. Learn about the new features in Apache Solr 9.1, including enhanced indexing time and memory efficiency for building HNSW graph data structures, dynamic switching between exact and approximate nearest neighbor search with pre-filtering capabilities, and integrations with Deep Learning models like BERT. Gain insights into how these cutting-edge developments can significantly improve your search functionality and user experience.
Syllabus
Neural Search Improvements with Apache Solr 9.1: Approximate Nearest Neighbo... Alessandro Benedetti
Taught by
Linux Foundation