Unleashing the Potential of Semantic Search: Enhancing OpenSearch in Drupal with Machine Learning

Session Room
Room 208 (Jakala)
Time Slot
Wed 11:25-11:55
Speaker(s)
alexandrdnlv
Session track
Innovation & The future
Experience level
Intermediate
Duration
30 min

In this session, we will embark on a comprehensive exploration of semantic search and its integration with OpenSearch in Drupal. We'll start by defining OpenSearch and examining its utilization within the Drupal framework. From there, we'll unravel the distinctions between keyword and semantic search, diving deep into the principles of embedding, the application of machine learning algorithms, and a KNN (K-Nearest Neighbors) approach. Finally, we'll unveil the concept of hybrid search, blending the best of both worlds. The session will culminate in a captivating live demo, showcasing practical implementation strategies.

Learning Objectives:
- Understand the fundamentals of OpenSearch and its role in Drupal;
- Differentiate between keyword and semantic search methodologies;
- Explore the principles of embedding and its significance in enhancing search capabilities;
- Gain insights into machine learning techniques, KNN for semantic search optimization;
- Learn how to integrate semantic search seamlessly into OpenSearch within the Drupal ecosystem;
- Acquire practical skills through a live demonstration of semantic search implementation.