Knowledge-driven data ecosystems toward data transparency
A data ecosystem (DE) offers a keystone-player or alliance-driven infrastructure that enables
the interaction of different stakeholders and the resolution of interoperability issues among …
the interaction of different stakeholders and the resolution of interoperability issues among …
Data-driven methodology for knowledge graph generation within the tourism domain
The tourism and hospitality sectors have become increasingly important in the last few years
and the companies operating in this field are constantly challenged with providing new …
and the companies operating in this field are constantly challenged with providing new …
Evaluating the impact of knowledge graph context on entity disambiguation models
Pretrained Transformer models have emerged as state-of-the-art approaches that learn
contextual information from the text to improve the performance of several NLP tasks. These …
contextual information from the text to improve the performance of several NLP tasks. These …
Knowledge4COVID-19: A semantic-based approach for constructing a COVID-19 related knowledge graph from various sources and analyzing treatments' toxicities
In this paper, we present Knowledge4COVID-19, a framework that aims to showcase the
power of integrating disparate sources of knowledge to discover adverse drug effects …
power of integrating disparate sources of knowledge to discover adverse drug effects …
A study of approaches to answering complex questions over knowledge bases
J Gomes Jr, RC de Mello, V Ströele… - … and Information Systems, 2022 - Springer
Question answering (QA) systems retrieve the most relevant answer to a natural language
question. Knowledge base question answering (KBQA) systems explore entities and …
question. Knowledge base question answering (KBQA) systems explore entities and …
Information extraction pipelines for knowledge graphs
In the last decade, a large number of knowledge graph (KG) completion approaches were
proposed. Albeit effective, these efforts are disjoint, and their collective strengths and …
proposed. Albeit effective, these efforts are disjoint, and their collective strengths and …
A semantics-aware transformer model of relation linking for knowledge base question answering
T Naseem, S Ravishankar… - Proceedings of the …, 2021 - aclanthology.org
Relation linking is a crucial component of Knowledge Base Question Answering systems.
Existing systems use a wide variety of heuristics, or ensembles of multiple systems, heavily …
Existing systems use a wide variety of heuristics, or ensembles of multiple systems, heavily …
A neuro-symbolic system over knowledge graphs for link prediction
Neuro-Symbolic Artificial Intelligence (AI) focuses on integrating symbolic and sub-symbolic
systems to enhance the performance and explainability of predictive models. Symbolic and …
systems to enhance the performance and explainability of predictive models. Symbolic and …
SPARQL-QA-v2 system for knowledge base question answering
MA Borroto, F Ricca - Expert Systems with Applications, 2023 - Elsevier
Accessing the large volumes of information available in public knowledge bases might be
complicated for those users unfamiliar with formal languages, such as the SPARQL query …
complicated for those users unfamiliar with formal languages, such as the SPARQL query …
Survey on english entity linking on wikidata: Datasets and approaches
Wikidata is a frequently updated, community-driven, and multilingual knowledge graph.
Hence, Wikidata is an attractive basis for Entity Linking, which is evident by the recent …
Hence, Wikidata is an attractive basis for Entity Linking, which is evident by the recent …