HighlightCurated by Aramai EditorialACM Computing Surveys

A Survey of Multi-modal Knowledge Graphs: Technologies and Trends

A comprehensive survey on multi-modal knowledge graphs and their applications.

The paper provides a rigorous definition of multi-modal knowledge graphs (MMKGs) and classifies existing approaches based on four fundamental challenges: representation, fusion, alignment, and translation. It aims to inspire researchers in the field of artificial intelligence by providing a reference for MMKGs. The survey highlights the potential of MMKGs in handling tasks that standard knowledge graphs cannot process.

Based on: A Survey of Multi-modal Knowledge Graphs: Technologies and Trends · ACM Computing Surveys

HighlightCurated by Aramai Editorialopenalex.org

Enhancing Retrieval Augmented Generation Systems with Knowledge Graphs

A paper proposing a comprehensive approach to enriching knowledge graphs.

The authors introduce a methodology that integrates key phrase extraction, node embedding generation, and an autonomous updating agent to create a connected knowledge graph. They also explore the incorporation of traditional vector search to enhance contextual understanding. The results show a substantial improvement in accuracy compared to traditional KG approaches.

Based on: Enhancing Retrieval Augmented Generation Systems with Knowledge Graphs

HighlightCurated by Aramai Editorialopenalex.org

TKG-RAG: A Retrieval-Augmented Generation Framework with Text-chunk Knowledge Graph

A retrieval-augmented generation framework that utilizes a text-chunk knowledge graph to improve performance.

The authors propose TKG-RAG, a framework that constructs a text-chunk knowledge graph automatically from domain text. This framework improves Retrieval-Augmented Generation (RAG) performance by addressing limitations such as noise and redundant information in retrieved text chunks. Comparative experiments show that TKG-RAG achieves better accuracy and F1 scores while reducing token consumption.

Based on: TKG-RAG: A Retrieval-Augmented Generation Framework with Text-chunk Knowledge Graph

HighlightCurated by Aramai Editorialopenalex.org

Scalable Extraction and Adoption of Shapes for Improving Data Quality and Query Processing in Knowledge Graphs

A thesis proposing techniques to improve data quality, efficient data access, and interoperability in Knowledge Graphs.

The resource proposes Quality Shapes Extraction (QSE) and SHACTOR to enhance data quality in Knowledge Graphs. It also introduces 'shapes statistics' for optimizing SPARQL query processing over KGs. The approach is demonstrated on both synthetic and real-world datasets, showing potential improvements in query performance.

Based on: Scalable Extraction and Adoption of Shapes for Improving Data Quality and Query Processing in Knowledge Graphs

HighlightCurated by Aramai EditorialInformation

Construction of Knowledge Graphs: Current State and Challenges

A research paper on the current state and challenges of constructing knowledge graphs.

The authors discuss the main graph models for knowledge graphs, introduce requirements for future construction pipelines, and evaluate the state-of-the-art. They identify areas in need of further research and improvement. The paper provides an overview of necessary steps to build high-quality knowledge graphs, including metadata management and quality assurance.

Based on: Construction of Knowledge Graphs: Current State and Challenges · Information

HighlightCurated by Aramai EditorialInternational journal of high school research

Empowering Large Language Model Reasoning : Hybridizing Layered Retrieval Augmented Generation and Knowledge Graph Synthesis

A paper proposing a novel methodology for enhancing complex LLM reasoning.

The paper proposes a hybrid approach combining layered retrieval augmented generation and knowledge graph synthesis to improve large language model (LLM) question answering. It extracts unstructured and structured properties of text to construct layered RAG pipelines, enabling the model to generate well-structured responses. The proposed framework integrates diverse RAG techniques and showcases its application in advanced answer generation using Wikipedia.

Based on: Empowering Large Language Model Reasoning : Hybridizing Layered Retrieval Augmented Generation and Knowledge Graph Synthesis · International journal of high school research

HighlightCurated by Aramai EditorialJournal of Biomedical Semantics

FAIR-Checker: supporting digital resource findability and reuse with Knowledge Graphs and Semantic Web standards

A web-based tool for assessing the FAIRness of metadata in digital resources.

FAIR-Checker is a tool that evaluates the FAIRness of metadata in digital resources using Semantic Web standards and technologies.,It offers two main facets: a 'Check' module for thorough metadata evaluation and recommendations, and an 'Inspect' module for improving metadata quality.,The tool was evaluated on over 25 thousand bioinformatics software descriptions.

Based on: FAIR-Checker: supporting digital resource findability and reuse with Knowledge Graphs and Semantic Web standards · Journal of Biomedical Semantics

HighlightCurated by Aramai EditorialProceedings of the ACM on Management of Data

PG-Schema: Schemas for Property Graphs

A formalism for specifying property graph schemas with flexible type definitions and expressive constraints.

The authors propose PG-Schema, a simple yet powerful formalism for specifying property graph schemas. It features flexible type definitions supporting multi-inheritance and expressive constraints based on the recently proposed PG-Keys formalism. The paper provides the formal syntax and semantics of PG-Schema, meeting principled design requirements grounded in contemporary property graph management scenarios.

Based on: PG-Schema: Schemas for Property Graphs · Proceedings of the ACM on Management of Data

HighlightCurated by Aramai EditorialarXiv (Cornell University)

Construction of Knowledge Graphs: State and Challenges

A research paper on the construction and updating of knowledge graphs.

The authors discuss graph models, requirements for KG construction pipelines, and necessary steps to build high-quality KGs. They evaluate the state-of-the-art and identify areas in need of further research. The paper provides an overview of the individual steps involved in creating and updating KGs from unstructured and structured data sources.

Based on: Construction of Knowledge Graphs: State and Challenges · arXiv (Cornell University)

HighlightCurated by Aramai EditorialArtificial Intelligence Review

Knowledge Graphs: Opportunities and Challenges

A systematic overview of knowledge graphs, focusing on opportunities and challenges.

This paper presents a comprehensive review of knowledge graphs, discussing their applications in AI systems and potential fields. It also explores technical challenges such as knowledge graph embeddings, acquisition, completion, fusion, and reasoning. The authors aim to provide insights for future research and development in the field.

Based on: Knowledge Graphs: Opportunities and Challenges · Artificial Intelligence Review

HighlightCurated by Aramai EditorialWU Research

How Does Knowledge Evolve in Open Knowledge Graphs?

This paper explores knowledge evolution in open knowledge graphs.

The authors investigate how knowledge evolves in open knowledge graphs, examining the dynamics of knowledge growth and change. They propose a framework for understanding and analyzing knowledge evolution in these graphs. The study contributes to the field by providing insights into the mechanisms driving knowledge evolution and its implications for knowledge graph management.

Based on: How Does Knowledge Evolve in Open Knowledge Graphs? · WU Research

HighlightCurated by Aramai EditorialJournal of Web Semantics

Streaming linked data: A survey on life cycle compliance

A survey on the life cycle compliance for Streaming Linked Data.

The paper surveys existing Stream Reasoning applications and proposes an updated life cycle for managing data streams on the Web. It identifies areas where the initial proposal needed reordering or splitting up and provides guidelines and best practices for each step. The updated life cycle serves as a blueprint for future SR applications.

Based on: Streaming linked data: A survey on life cycle compliance · Journal of Web Semantics