A Review of Hybrid Search Architectures: Integrating Keyword and Semantic Search to Optimize Query Relevance

A Review of Hybrid Search Architectures:  Integrating Keyword and Semantic Search to Optimize Query Relevance

Syed Arham Akheel

Senior Solutions Architect, Data Science Dojo

Bellevue, WA

arhamakheel@yahoo.com

Abstract—The advent of semantic search alongside the traditional robustness of keyword search systems has established an intriguing dichotomy within the landscape of information retrieval. While keyword based methods excel in terms of specificity, semantic models offer contextual richness and intent awareness. However, each paradigm faces challenges in harnessing the strengths of the other. This paper investigates a hybrid search model that integrates both keyword and semantic search techniques, aiming to optimize relevance, interpretability, and user experience in complex information seeking scenarios. We present an innovative hybrid architecture, conduct a comprehensive evaluation of its performance, and discuss its implications for information retrieval in specialized domains such as healthcare and education.

Index Terms—Hybrid Search, Keyword Search, Semantic Search, Information Retrieval, Natural Language Processing, Search Architectures