Large Language Models, Knowledge Graphs and Search Engines: A Crossroads for Answering Users' Questions

https://arxiv.org/abs/2501.06699

This research paper examines the interplay between large language models (LLMs), knowledge graphs (KGs), and search engines (SEs) in fulfilling user information needs. The authors analyze the strengths and weaknesses of each technology across various dimensions, including correctness, completeness, and freshness. A taxonomy of user information needs is presented, showing how each technology—individually or in combination—addresses different query types (e.g., factual, explanatory, or advisory). Finally, the paper proposes research directions for integrating these technologies synergistically to improve information retrieval and user experience.