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arXiv:2609.37749 · RAG 检索增强

Towards Semi-Automatically Comparing Keyword-Based and Semantic Search Accuracy

Towards Semi-Automatically Comparing Keyword-Based and Semantic Search Accuracy

类型：arxiv
标识：2609.37749
链接：http://arxiv.org/abs/2609.37749v1
主分类：rag
形态：method
TLDR：The increasing importance of Information Retrieval (IR) in managing large datasets has highlighted significant limitations in traditional keyword-based search systems. Context-aware chat-based search methods, such as Retrieval Augmented Generation (RAG), have recently emerged, but their evaluation compared to keyword-based systems often relies on subjective user feedback. A rigorous, quantitative comparison between these paradigms remains lacking. This work introduces a novel, preliminary framework to quantitatively assess IR accuracy of search systems that produce different output formats, su
待LLM分类：否
来源文件：
/inbox/tom/_candidates/2026-09-30-agent-rag-longcontext-candidates.json

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arXiv

2609.37749

TLDR

The increasing importance of Information Retrieval (IR) in managing large datasets has highlighted significant limitations in traditional keyword-based search systems. Context-aware chat-based search methods, such as Retrieval Augmented Generation (RAG), have recently emerged, but their evaluation compared to keyword-based systems often relies on subjective user feedback. A rigorous, quantitative comparison between these paradigms remains lacking. This work introduces a novel, preliminary framework to quantitatively assess IR accuracy of search systems that produce different output formats, su

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