Graph Search
Graph search focuses on efficiently finding paths or patterns within complex graph structures, aiming to optimize search speed and solution quality. Current research emphasizes developing novel algorithms, including those leveraging reinforcement learning, graph neural networks, and hybrid approaches combining graph search with techniques like trajectory optimization or retrieval-augmented generation. These advancements are improving performance in diverse applications, such as multi-agent systems, robot motion planning, and knowledge graph-based information retrieval, leading to more efficient and robust solutions for various real-world problems.
Papers
A Knowledge Graph-Based Search Engine for Robustly Finding Doctors and Locations in the Healthcare Domain
Mayank Kejriwal, Hamid Haidarian, Min-Hsueh Chiu, Andy Xiang, Deep Shrestha, Faizan Javed
From Data to Dialogue: Leveraging the Structure of Knowledge Graphs for Conversational Exploratory Search
Phillip Schneider, Nils Rehtanz, Kristiina Jokinen, Florian Matthes