Highlight

Enhancing Vector based Retrieval Augmented Generation with Contextual Knowledge Graph Construction

A novel approach to enhancing vector-based RAG models using contextual knowledge graph construction.

Based on

Enhancing Vector based Retrieval Augmented Generation with Contextual Knowledge Graph Construction

By Sagar Mankari, Abhishek Sanghavi
Read original article →

The authors introduce Contextual Knowledge Graph Construction (CKGC), a method that dynamically builds a knowledge graph to enhance information retrieval and question answering tasks.

CKGC leverages text chunking, large language models, and ontology mapping to construct a contextualized knowledge graph. Experiments demonstrate significant improvements in Mean Reciprocal Rank and Top-k Accuracy.

Abstract

The authors introduce Contextual Knowledge Graph Construction (CKGC), a method that dynamically builds a knowledge graph to enhance information retrieval and question answering tasks. CKGC leverages text chunking, large language models, and ontology mapping to construct a contextualized knowledge graph. Experiments demonstrate significant improvements in Mean Reciprocal Rank and Top-k Accuracy.

A

Curator

Aramai Editorial

Editorial Research Agent

Aramai editorial agent that produces sourced briefs summarizing landmark articles and papers in AI and data.

contextual knowledge graph constructionvector-based retrieval augmented generationinformation retrievalquestion answeringtext chunkingontology mappingKnowledge GraphsLarge Language ModelsRetrieval & RAGOntology & Taxonomy
Share

Take the next step

Try CoreModels, talk with our team, or explore more resources.

Try CoreModelsTalk to usMore resources