Knowledge Graph
Knowledge graphs (KGs) are structured representations of information, aiming to organize data into interconnected entities and relationships to facilitate knowledge discovery and reasoning. Current research heavily focuses on integrating KGs with large language models (LLMs) to enhance question answering, knowledge graph completion, and other knowledge-intensive tasks, often employing retrieval-augmented generation (RAG) and graph neural network architectures. This integration improves the accuracy and efficiency of various applications, ranging from legal article recommendation and medical diagnosis to supporting legislative processes and scholarly research. The resulting advancements have significant implications for diverse fields requiring complex information processing and reasoning.
Papers - Page 38
Context-aware explainable recommendations over knowledge graphs
Jinfeng Zhong, Elsa NegreNatural Language Processing for Drug Discovery Knowledge Graphs: promises and pitfalls
J. Charles G. Jeynes, Tim James, Matthew CorneyNuTrea: Neural Tree Search for Context-guided Multi-hop KGQA
Hyeong Kyu Choi, Seunghun Lee, Jaewon Chu, Hyunwoo J. Kim
Linking Surface Facts to Large-Scale Knowledge Graphs
Gorjan Radevski, Kiril Gashteovski, Chia-Chien Hung, Carolin Lawrence, Goran GlavašUniversal Knowledge Graph Embeddings
N'Dah Jean Kouagou, Caglar Demir, Hamada M. Zahera, Adrian Wilke, Stefan Heindorf, Jiayi Li, Axel-Cyrille Ngonga NgomoA Study on Knowledge Graph Embeddings and Graph Neural Networks for Web Of Things
Rohith Teja Mittakola, Thomas HassanKnowledge-Induced Medicine Prescribing Network for Medication Recommendation
Ahmad Wisnu Mulyadi, Heung-Il Suk
Leveraging Knowledge Graphs for Orphan Entity Allocation in Resume Processing
Aagam Bakliwal, Shubham Manish Gandhi, Yashodhara HaribhaktaEmulating the Human Mind: A Neural-symbolic Link Prediction Model with Fast and Slow Reasoning and Filtered Rules
Mohammad Hossein Khojasteh, Najmeh Torabian, Ali Farjami, Saeid Hosseini, Behrouz Minaei-Bidgoli
Solving Hard Analogy Questions with Relation Embedding Chains
Nitesh Kumar, Steven SchockaertMulti-view Contrastive Learning for Entity Typing over Knowledge Graphs
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang, Ru Li, Jeff Z. PanA Benchmark for Semi-Inductive Link Prediction in Knowledge Graphs
Adrian Kochsiek, Rainer GemullaDescriptive Knowledge Graph in Biomedical Domain
Kerui Zhu, Jie Huang, Kevin Chen-Chuan ChangSystematic Assessment of Factual Knowledge in Large Language Models
Linhao Luo, Thuy-Trang Vu, Dinh Phung, Gholamreza Haffari
Integrating 3D City Data through Knowledge Graphs
Linfang Ding, Guohui Xiao, Albulen Pano, Mattia Fumagalli, Dongsheng Chen, Yu Feng, Diego Calvanese, Hongchao Fan, Liqiu MengQuery2Triple: Unified Query Encoding for Answering Diverse Complex Queries over Knowledge Graphs
Yao Xu, Shizhu He, Cunguang Wang, Li Cai, Kang Liu, Jun ZhaoKG-GPT: A General Framework for Reasoning on Knowledge Graphs Using Large Language Models
Jiho Kim, Yeonsu Kwon, Yohan Jo, Edward ChoiAccurate prediction of international trade flows: Leveraging knowledge graphs and their embeddings
Diego Rincon-Yanez, Chahinez Ounoughi, Bassem Sellami, Tarmo Kalvet, Marek Tiits, Sabrina Senatore, Sadok Ben Yahia