This article is approximately 5500 words long and is recommended for an 11-minute read. This paper proposes a pseudo-graph structure by relaxing the pattern constraints on data and relationships in traditional KGs. Paper Title: Empowering Large Language Models to Set up a Knowledge Retrieval Indexer via Self-Learning Author Affiliation: Renmin University of China (RUC), Shanghai … Read more
Source: DeepHub IMBA This article is approximately 4600 words long and is recommended to be read in 10 minutes. In this article, we will combine text and knowledge graphs to enhance the performance of our RAG. In our previous articles, we introduced examples of combining knowledge graphs with RAG. In this article, we will combine … Read more
Source: DeepHub IMBA This article is about 1600 words long and is recommended to be read in 5 minutes. Retrieval-Augmented Generation is a technical approach aimed at enhancing the performance of large language models. Overview of Retrieval-Augmented Generation (RAG) Technology Retrieval-Augmented Generation (RAG) is a technical method aimed at enhancing the performance of Large Language … Read more
Abstract: The transition from traditional RAG to Graph RAG enhances large language models by integrating knowledge graphs, enabling them to provide more detailed and accurate responses to complex queries. The effectiveness of Graph RAG also depends on the quality and breadth of the underlying knowledge graph and the engineering aspects of RAG. Main Points: – … Read more
Machine Heart Reprint Authors:Han Xu, Gao Tianyu, Liu Zhiyuan This article is written by Professor Liu Zhiyuan from Tsinghua University and his students Han Xu and Gao Tianyu, introducing the topic of knowledge graphs. The article reviews the development of the knowledge graph field and summarizes recent research progress. It has been authorized for reprint … Read more
With the development of artificial intelligence research, knowledge graphs (KGs) have attracted wide attention from both academia and industry. As a representation of semantic relationships between entities, knowledge graphs play an important role in natural language processing (NLP) and have seen rapid promotion and widespread adoption in recent years. Given the increasing workload of research … Read more
The human-computer interaction feature allows us to involve the user in the decision-making process of the graph. The following guide demonstrates how to implement human-computer interaction workflows in the graph. The human-computer interaction workflow integrates user input into automated processes, allowing for decision-making, validation, or correction at critical stages. This is particularly useful in applications … Read more
Learn how to converse with AI here Get 100,000 words of free AI learning materials In today’s rapidly advancing technological era, artificial intelligence (AI) is no longer a concept from science fiction but has genuinely integrated into our lives. From voice assistants on smartphones to intelligent control of smart home devices, and the convenient functions … Read more