Search Query Expansion Using Natural Language Processing and Machine Learning

Explore advanced techniques for search query expansion using natural language processing and machine learning in this informative 58-minute video presentation. Learn about the Agolo correlation service, which employs unsupervised machine learning to identify implicit relationships among terms within content sets. Discover how this approach can be applied to enterprise search challenges, particularly in complex technical disciplines. Gain insights into data-driven patterns, business challenges, and motivations behind query expansion. Examine various search query techniques, corpus-based query expansion, and the implementation of dynamic search. Understand the matching process and participate in a Q&A session to deepen your knowledge of this innovative approach to improving search functionality in enterprise environments.

– Intro
– Aglo correlation service
– Data-driven patterns in protective effects
– Business challenge
– Motivation
– Query expansion
– Search queries
– Corpus-base QE
– Aglo correlation service
– Dynamic search
– Matching
– QnA