Hybrid Retrieval

Sohu Tech Products

Mar 19, 2025 · Databases

Redis Vector Search Technology for AI Applications: Implementation and Best Practices

The article explains how Redis vector search, powered by RedisSearch’s FLAT and HNSW algorithms and supporting various data types and precisions, enables fast AI-driven similarity queries for text, image, and audio, and provides implementation guidance, optimization tips, and a real‑world customer‑service use case.

AI applicationsDatabase OptimizationHNSW

0 likes · 17 min read

Redis Vector Search Technology for AI Applications: Implementation and Best Practices

DataFunSummit

Oct 21, 2024 · Artificial Intelligence

Retrieval‑Augmented Generation (RAG) for Office Applications: Architecture, Challenges, and Practical Practices

This article introduces Retrieval‑Augmented Generation (RAG) as a solution to the hallucination, freshness, and data‑privacy issues of large language models, details its modular architecture, explains the layered system design and hybrid retrieval pipeline, and shares the practical challenges and engineering tricks encountered when deploying RAG in enterprise office scenarios.

AIHybrid RetrievalRAG

0 likes · 19 min read

Retrieval‑Augmented Generation (RAG) for Office Applications: Architecture, Challenges, and Practical Practices

Baidu Geek Talk

Nov 29, 2021 · Artificial Intelligence

Pretrained Models for First-Stage Information Retrieval: A Comprehensive Review

This comprehensive review by Dr. Fan Yixing surveys how pretrained language models have transformed first‑stage information retrieval, tracing the shift from traditional term‑based methods to neural sparse, dense, and hybrid approaches, and discussing key challenges such as hard‑negative mining, joint indexing‑representation learning, and generative‑discriminative training.

Hybrid RetrievalNeural IRSparse Retrieval

0 likes · 15 min read

Pretrained Models for First-Stage Information Retrieval: A Comprehensive Review