HighlightCurated by Aramai Editorial

Knowledge representation and reasoning in personal knowledge graphs

A chapter discussing the semantic web stack and its application to personal knowledge graphs.

The authors describe the semantic web stack, a set of open standards for representing and reasoning with knowledge graphs.,They discuss projects using these standards to build personal knowledge graphs that interoperate with other knowledge graphs on the web.,Related standards for describing rules and policies are also discussed.

Based on: Knowledge representation and reasoning in personal knowledge graphs · Institution of Engineering and Technology eBooks

HighlightCurated by Aramai Editorial

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 Editorial

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 Editorial

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 Editorial

The SAREF Pipeline and Portal—An Ontology Verification Framework

A framework for ontology verification presented in a lecture notes publication.

This paper introduces the SAREF pipeline and portal, an ontology verification framework. The authors describe the framework's components and its application to ontology validation. The framework is designed to facilitate the verification of ontologies and their integration with other knowledge graphs.

Based on: The SAREF Pipeline and Portal—An Ontology Verification Framework · Lecture notes in computer science

HighlightCurated by Aramai Editorial

Resilience and Resilient Systems of Artificial Intelligence: Taxonomy, Models and Methods

A study on the resilience of artificial intelligence systems, including a taxonomy and analysis of relevant scientific publications.

The paper presents a systematic approach to analyzing AI system resilience, identifying sources of threats, and methods for ensuring resilience properties. It confirms the potential to create resilient AI systems by configuring architecture and learning scenarios. The study provides a roadmap for establishing technical requirements and assessing existing AI system resilience.

Based on: Resilience and Resilient Systems of Artificial Intelligence: Taxonomy, Models and Methods · Algorithms

HighlightCurated by Aramai Editorial

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 Editorial

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

HighlightCurated by Aramai Editorial

Ontology Repositories and Semantic Artefact Catalogues with OntoPortal Technology

A paper on the OntoPortal Alliance consortium's platforms for ontology management.

The OntoPortal Alliance consortium provides common platforms for receiving, hosting, serving, aligning, and enabling reuse of ontologies and semantic artefacts.,These platforms make ontologies FAIR (Findable, Accessible, Interoperable, Reusable).,They address the growing need for governance of exploding number of semantic artefacts in science.

Based on: Ontology Repositories and Semantic Artefact Catalogues with OntoPortal Technology · LNCS / ISWC

HighlightCurated by Aramai Editorial

GPT-4 Technical Report

A technical report on the GPT-4 model by OpenAI.

The report introduces the MFOUR Vibe Framework (MVF), a platform-agnostic architectural standard for transforming probabilistic natural language intent into deterministic software artifacts.,The MVF consists of a five-layer topology, including Kernel Identity, Synaptic Routing, Interface Contracts, Context Anchoring, and Artifact Generation.,This framework aims to address the inherent stochasticity in Large Language Models (LLMs) and provide determinism and auditability.

Based on: GPT-4 Technical Report

HighlightCurated by Aramai Editorial

QSE: Extraction of Validating Shapes from Very Large Knowledge Graphs

Proposes a Quality Shapes Extraction approach for extracting validating shapes in very large knowledge graphs.

The paper presents the QSE approach, which uses SHACL/ShEx to extract validating shapes from large knowledge graphs. It provides both exact and approximate solutions with confidence metrics. The authors achieve significant speed improvements and spurious shape reductions on DBpedia.

Based on: QSE: Extraction of Validating Shapes from Very Large Knowledge Graphs · VLDB Endowment

HighlightCurated by Aramai Editorial

Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence

A research paper on the need for explainable AI methods to improve trust in AI models.

The authors discuss the challenges of understanding AI model decision-making and the importance of XAI. They review existing survey papers and highlight areas where further research is needed. The paper aims to provide a comprehensive overview of current knowledge and future directions in XAI.

Based on: Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence