HighlightCurated by Aramai EditorialVBN Forskningsportal (Aalborg Universitet)

Knowledge Graph Exploration Systems: are we lost?

A position paper on the challenges and requirements for effective knowledge graph exploration systems.

The authors discuss the limitations of current knowledge graph data management systems in meeting the needs of KG exploration use cases. They present an overview of state-of-the-art approaches, identify unmet requirements, and highlight promising research directions.

Based on: Knowledge Graph Exploration Systems: are we lost? · VBN Forskningsportal (Aalborg Universitet)

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 EditorialGhent University Academic Bibliography (Ghent University)

Improving and assessing data quality of knowledge graphs

A dissertation on improving and assessing data quality in knowledge graphs.

This dissertation focuses on improving data quality and assessing semantic quality of knowledge graphs. It investigates two challenges: including data transformations to clean the data, and evaluating the quality of knowledge graphs on both data values and semantic relationships.

Based on: Improving and assessing data quality of knowledge graphs · Ghent University Academic Bibliography (Ghent University)

HighlightCurated by Aramai Editorialopenalex.org

Ontology-Based Data Access: A Survey

A survey on the framework of ontology-based data access for providing user-friendly access to relational data sources.

The paper discusses the main ingredients, key results, techniques, applications, and future challenges of ontology-based data access. It focuses on relational data sources and provides a comprehensive overview of the field. The authors present the theoretical foundations, practical techniques, and potential applications of this semantic paradigm.

Based on: Ontology-Based Data Access: A Survey

HighlightCurated by Aramai Editorialopenalex.org

Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment

A translation-based model for multilingual knowledge graph embeddings.

The paper proposes MTransE, a model that provides transitions for each embedding vector to its cross-lingual counterparts in other spaces. It can be trained on partially aligned graphs and preserves the key properties of monolingual embeddings. The experiments show promising results on cross-lingual entity matching and triple-wise alignment verification.

Based on: Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment

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 EditorialLecture notes in computer science

Applying KAoS Services to Ensure Policy Compliance for Semantic Web Services Workflow Composition and Enactment

Paper on applying KAoS services to ensure policy compliance in semantic web services workflow composition and enactment.

This paper explores the application of KAoS services to ensure policy compliance in semantic web services. The authors investigate how KAoS can be used to manage policies and ensure that they are enforced during the composition and enactment of workflows. The paper discusses the benefits and challenges of using KAoS for this purpose, including its ability to provide a flexible and scalable approach to policy management.

Based on: Applying KAoS Services to Ensure Policy Compliance for Semantic Web Services Workflow Composition and Enactment · Lecture notes in computer science