Webinar
Milvus Hybrid Search: Combining Keyword Precision with Semantic Power for Next-Gen Data Retrieval
Mar 27, 2025 10:00 AM Pacific
Mar 27, 2025 01:00 PM EasternZilliz Webinar | Zoom
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About this webinar
This webinar demonstrates a unified approach to document retrieval by combining advanced web crawling with a hybrid search architecture that leverages both full text and dense vector search within Milvus. Participants will see how Crawl4AI is used to extract documentation which is then ingested into Milvus. The system utilizes Milvus’ full text search capabilities—powered by built-in BM25 relevance scoring—to handle keyword matching, while dense vector search is employed for semantic similarity. Together, these methods address the challenge of accurately retrieving relevant information.
Topics Covered
- Data Extraction with Crawl4AI: Techniques for scraping documentation for python and npm libraries.
- Milvus Full Text Search: Internal mechanisms including text tokenization, sparse embedding generation, and BM25 scoring.
- Milvus Dense Vector Search: Use of ANN search and efficient indexing strategies to rapidly compute semantic similarity.
- Hybrid Search Integration: Method of merging keyword-based and vector-based retrieval to improve accuracy and coverage.
Meet the Speaker
Join the session for live Q&A with the speaker
Erbli Kuka
Data / AI Engineer at datamax.ai
Erbli Kuka is a Data / AI Engineer at datamax.ai specializing in ML/AI development and integration. He has gained deep insights into the TRANSFORMERS architecture, attention mechanisms, and other critical areas of machine learning. Passionate about ML, Erbli is committed to advancing his career and ultimately leading teams to create innovative solutions in cloud development and AI.