HighlightCurated by Aramai EditorialData Intelligence (MIT Press)

The W3C Data Catalog Vocabulary Version 2: Rationale Design Principles and Uptake

W3C RDF vocabulary for data catalog interoperability.

DCAT v2 addresses gaps identified through implementation experience across communities, building on the 2014 W3C Recommendation. It supports wide adoption, especially with FAIR data principles. The vocabulary enables data catalog interoperability.

Based on: The W3C Data Catalog Vocabulary Version 2: Rationale Design Principles and Uptake · Data Intelligence (MIT Press)

HighlightCurated by Aramai EditorialIEEE Transactions on Neural Networks and Learning Systems

A Survey on Knowledge Graphs: Representation, Acquisition, and Applications

Comprehensive review of knowledge graph research topics and recent breakthroughs.

The paper provides a survey of knowledge graphs, covering representation learning, acquisition, and applications.,It reviews various aspects of knowledge graph embedding, including representation space, scoring function, encoding models, and auxiliary information.,The authors also explore emerging topics such as metarelational learning, commonsense reasoning, and temporal knowledge graphs.

Based on: A Survey on Knowledge Graphs: Representation, Acquisition, and Applications · IEEE Transactions on Neural Networks and Learning Systems

HighlightCurated by Aramai EditorialACM Computing Surveys

Knowledge Graphs

Comprehensive introduction to knowledge graphs.

The article provides an overview of knowledge graphs, their applications, and challenges.,It motivates and contrasts various graph-based data models and query languages.,The authors explain how knowledge can be represented and extracted using deductive and inductive techniques.

Based on: Knowledge Graphs · ACM Computing Surveys

HighlightCurated by Aramai EditorialJournal of Biomedical Semantics

Enabling ad-hoc reuse of private data repositories through schema extraction

A paper proposing a configurable and automated schema extraction approach for RDF triple stores.

The authors present an approach to extract and publish data schemas from private repositories, enabling SPARQL query formulation without direct access. Evaluation with four datasets shows the effectiveness of this method in deriving concise and task-relevant schemas. This approach can facilitate reuse of data from previously inaccessible sources.

Based on: Enabling ad-hoc reuse of private data repositories through schema extraction · Journal of Biomedical Semantics

HighlightCurated by Aramai EditorialJournal of Web Semantics

Completeness and consistency analysis for evolving knowledge bases

This paper presents an analysis on completeness and consistency in evolving knowledge bases.

The authors propose a framework to analyze the completeness and consistency of evolving knowledge bases. They introduce metrics to measure these aspects and apply them to several case studies. The results demonstrate the effectiveness of their approach in identifying issues with knowledge base evolution.

Based on: Completeness and consistency analysis for evolving knowledge bases · Journal of Web Semantics

HighlightCurated by Aramai EditorialSemantic Web

Linked data quality of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO

A survey comparing the data quality criteria of five large knowledge graphs.

The paper compares the data quality of five large knowledge graphs: DBpedia, Freebase, OpenCyc, Wikidata, and YAGO. It provides a framework for analyzing and selecting the most suitable graph for a given setting. The authors propose data quality criteria to evaluate these graphs.

Based on: Linked data quality of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO · Semantic Web

HighlightCurated by Aramai Editorialopenalex.org

Semantic Parsing via Staged Query Graph Generation: Question Answering with Knowledge Base

This paper presents a method for question answering with knowledge bases using staged query graph generation.

The authors propose a semantic parsing approach that generates query graphs in stages to answer questions based on a knowledge base. This method improves the accuracy of question answering by iteratively refining the query graph. The proposed approach is evaluated on several benchmarks and shows competitive results compared to state-of-the-art methods.

Based on: Semantic Parsing via Staged Query Graph Generation: Question Answering with Knowledge Base

HighlightCurated by Aramai EditorialarXiv (Cornell University)

Embedding Entities and Relations for Learning and Inference in Knowledge Bases

A survey on approaches to learning first-order logic rules over knowledge graphs.

This paper reviews state-of-the-art systems for learning first-order logic rules over knowledge graphs. It conducts a comparative analysis of various approaches, including ILP-based, statistical path generalisation, and neuro-symbolic methods. The authors highlight important application scenarios of rule learning in knowledge graph completion, fact checking, and other research areas.

Based on: Embedding Entities and Relations for Learning and Inference in Knowledge Bases · arXiv (Cornell University)

HighlightCurated by Aramai EditorialJournal of Artificial Intelligence Research

Text Relatedness Based on a Word Thesaurus

A paper proposing a measure of semantic relatedness between texts using word-to-word semantic links.

The authors present a new approach to measuring text relatedness based on implicit semantic links between words.,They introduce Omiotis, a measure that capitalizes on the semantic relatedness between individual words and extends it to text-to-text relatedness.,Experimental evaluation shows that this method outperforms lexicon-based methods in selected tasks.

Based on: Text Relatedness Based on a Word Thesaurus · Journal of Artificial Intelligence Research

HighlightCurated by Aramai EditorialJournal of Web Semantics

YAGO: A Large Ontology from Wikipedia and WordNet

A large ontology constructed from Wikipedia and WordNet.

YAGO is a large-scale ontology that integrates information from Wikipedia and WordNet.,It was developed by Fabian M. Suchanek, Gjergji Kasneci, and Gerhard Weikum in 2008.,The ontology covers a wide range of entities and relationships, making it a valuable resource for knowledge graph applications.

Based on: YAGO: A Large Ontology from Wikipedia and WordNet · Journal of Web Semantics